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Readme.md ADDED
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+ # Datasets Repository
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+
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+ This folder contains three graph datasets saved as pickle files, used for the evaluation of methods. Each dataset is a list of dictionaries containing the task name, initial state, and goal state represented as NetworkX graphs. Additionally, each dictionary includes specific information relevant to the dataset.
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+
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+ | **Data** | **Number of Tasks** | **Mean nodes** | **Actions** |
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+ |---------------------|-----------|-----------|-------------|
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+ | SayPlan Office | 25 | 202.6 | 2.1 |
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+ | Behaviour-1K | 186 | 12.1 | 4.9 |
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+ | VirtualHome | 347 | 195.7 | 1.6 |
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+
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+ **Table 1:** Dataset comparison. *Actions* represent the mean number of nodes changed between the initial and goal graph.
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+
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+
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+ To load a dataset, use the following code snippet:
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+
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+ ```python
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+
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+ import pickle
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+
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+ with open('./datasets/<name>.pkl', 'rb') as file:
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+ tasks = pickle.load(file)
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+
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+ ```
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+ ## SayPlan Office
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+
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+ The SayPlan Office dataset represents graphs and tasks defined in [SayPlan](https://sayplan.github.io/). Each task consists of a dictionary with the following structure:
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+
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+ - `name`: The name of the task.
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+ - `human`: Human-readable task description (same as `name` for SayPlan).
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+ - `detailed`: Detailed task description (same as `name` for SayPlan).
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+ - `init`: Initial state as a NetworkX graph.
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+ - `goal`: Goal state as a NetworkX graph.
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+ - `actions`: A list of ground-truth actions to complete the task.
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+
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+ ## Behaviour-1K
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+
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+ The Behaviour-1K dataset represents tasks defined in [Behaviour1K](https://behavior.stanford.edu/knowledgebase/tasks/index.html). For each task defined in BDDL, a subgraph was constructed to represent the environment. Using this subgraph, the goal graph was created, and human-readable as well as detailed task descriptions were added.
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+
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+ The dataset contains a total of 186 tasks, each represented by a dictionary with the following structure:
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+
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+ - `name`: The name of the task from Behaviour1K.
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+ - `human`: Human-readable task description.
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+ - `detailed`: Detailed task description.
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+ - `init`: Initial state as a NetworkX graph.
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+ - `goal`: Goal state as a NetworkX graph.
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+
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+ ## VirtualHome RobotHow
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+
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+ The VirtualHome dataset represents tasks from the [RobotHow](http://virtual-home.org/tools/explore.html) dataset. For each task, the VirtualHome graph was reconstructed into a structure compatible with our methods. This was achieved using the `graph_parser.py` script available in the `utils` folder of the repository.
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+
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+ Additionally, an `ids` dictionary maps nodes from the initial NetworkX graph to VirtualHome IDs. For example, the node `('fridge', 1)` in the initial graph corresponds to the fridge node with ID 67 in the VirtualHome backend graph. This mapping is useful when using the dataset with the VirtualHome simulator.
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+
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+ Each task is represented by a dictionary with the following structure:
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+
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+ - `name`: The name of the task from RobotHow.
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+ - `human`: Human-readable task description. (Same as name for RobotHow)
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+ - `detailed`: Detailed task description.
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+ - `init`: Initial state as a NetworkX graph.
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+ - `goal`: Goal state as a NetworkX graph.
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+ - `ids`: Mapping of nodes to VirtualHome IDs.
__init__.py ADDED
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+ from .datasets import SayPlanOffice, VirtualHome, Behaviour1K
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+ from .validator import validate_plan
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+
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+ __all__ = ["SayPlanOffice","VirtualHome","validate_plan", "Behaviour1K"]
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+
behaviour1k/behaviour177.json ADDED
The diff for this file is too large to render. See raw diff
 
behaviour1k/behaviour177.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:9473e4c1eff393ea6bcbdb7e90e83f0499c50def7a88c792b81670bd8a848f25
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+ size 445047
behaviour1k/create_pkl.py ADDED
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+ import json
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+ import pickle
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+ import networkx as nx
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+ import matplotlib.pyplot as plt
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+ # Define file paths
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+ JSON = './behaviour177.json'
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+ PKL = 'behaviour177.pkl'
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+
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+ def add_edges(G):
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+ for node_name in G.nodes:
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+ node = G.nodes[node_name]
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+ match node['type']:
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+ case 'place':
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+ G.add_edge(node_name,('scene',1))
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+ case 'asset':
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+ G.add_edge(node_name,node['place'])
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+ case 'object':
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+ G.add_edge(node_name,node['related_to'])
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+ case 'agent':
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+ G.add_edge(node_name,node['location'])
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+ case 'scene':
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+ pass
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+ case _:
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+ print(f"Unknown node type: {node['type']}")
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+
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+ def parse_json(tasks):
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+ graph = nx.Graph()
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+ graph.add_node(('scene',1), name =task['name'], type='scene')
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+ for node in tasks:
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+ if node['type'] == 'place':
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+ graph.add_node((node['name'], node['id']), type='place')
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+ if node['type'] == 'asset':
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+ graph.add_node((node['name'], node['id']), place=(node['place'],node['place_id']), states=node['states'], affordances =node['affordances'], properties=[], type = 'asset')
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+ if node['type'] == 'object':
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+ graph.add_node((node['name'], node['id']), relation=node['relation'], related_to=(node['related_to'][0],node['related_to'][1]), states=node['states'], affordances =node['affordances'], properties=[], type = 'object')
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+ if node['type'] == 'agent':
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+ graph.add_node(('agent',1), location=(node['location'][0],node['location'][1]), holding='', type='agent')
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+ add_edges(graph)
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+ return graph
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+
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+ if __name__ == "__main__":
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+ # Load JSON data
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+ with open(JSON, 'r') as json_file:
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+ input_data = json.load(json_file)
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+
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+ output_data = []
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+ i=0
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+ for task in input_data:
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+ i+=1
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+ init_graph = parse_json(task['init'])
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+ goal_graph = parse_json(task['goal'])
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+ entity = {
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+ 'id' : i,
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+ 'name':task['name'],
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+ 'task':task['task'],
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+ 'init': init_graph,
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+ 'goal': goal_graph,
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+ }
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+ output_data.append(entity)
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+ # Save data to a pickle file
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+ with open(PKL, 'wb') as pkl_file:
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+ pickle.dump(output_data, pkl_file)
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+
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+ print(f"Data from {JSON} has been saved to {PKL}.")
datasets.py ADDED
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+ import pickle
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+ import os
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+
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+ class Dataset:
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+ def __init__(self, name, path):
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+ self.name = name
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+ self.path = os.path.abspath(path)
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+ self.tasks = None
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+
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+ def get_tasks(self):
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+ with open(self.path, "rb") as file:
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+ self.tasks = pickle.load(file)
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+ return self.tasks
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+
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+ current_dir = os.path.dirname(os.path.abspath(__file__))
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+
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+ SayPlanOffice = Dataset("office29", os.path.join(current_dir, "office", "office29.pkl"))
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+ Behaviour1K = Dataset("behaviour177", os.path.join(current_dir, "behaviour1k", "behaviour177.pkl"))
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+ VirtualHome = Dataset("virtualhome317", os.path.join(current_dir, "virtualhome", "virtualhome317.pkl"))
office/create_pkl.py ADDED
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+ '''
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+ This script processes `office_changes.json` to generate a dataset of office manipulation tasks.
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+
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+ The `CHANGES_DESCRIPTION_FILE` file contains a list of tasks, each with:
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+ - "name": A natural language description.
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+ - "init_conditions": An array of conditions to define the starting world state. null if no changes
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+ - "goal_conditions": An array of conditions that describe the target world state.
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+ - "actions": A sequence of actions to transition from the initial to the goal state.
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+ '''
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+ import json
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+ import pickle
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+ from office_graph import office_graph, add_edges
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+ import copy
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+
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+ CHANGES_DESCRIPTION_FILE = 'office_changes.json'
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+ OUT_FILENAME = 'office29.pkl'
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+
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+ def change_node(node, condition, graph):
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+ if condition.get("holding", False):
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+ graph.nodes[node]['holding'] = (condition["holding"]['name'], condition["holding"]['id'])
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+
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+ if condition["relation"]:
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+ graph.nodes[node]['related_to'] = (condition["related_to"]["name"], condition["related_to"]["id"])
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+ graph.nodes[node]['relation'] = condition["relation"]
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+
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+ if condition["states"]:
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+ states = condition.get("states", [])
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+ for state in states:
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+ if state not in graph.nodes[node]['states']:
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+ graph.nodes[node]['states'].append(state)
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+ if state == 'off':
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+ graph.nodes[node]['states'].remove('on')
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+ if state == 'on':
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+ graph.nodes[node]['states'].remove('off')
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+ if state == 'closed':
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+ graph.nodes[node]['states'].remove('open')
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+ if state == 'open':
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+ graph.nodes[node]['states'].remove('closed')
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+
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+ if __name__ == "__main__":
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+ # Load the JSON file
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+ with open(CHANGES_DESCRIPTION_FILE, "r") as file:
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+ tasks = json.load(file)
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+
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+ dataset = []
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+ i=0
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+ for task in tasks:
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+ i+=1
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+ name = task["name"]
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+ init_graph = copy.deepcopy(office_graph)
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+ goal_graph = copy.deepcopy(office_graph)
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+ # Process initial conditions
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+ if task['init_conditions']:
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+ for condition in task.get("init_conditions", []):
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+ node = (condition["node"]["name"], condition["node"]["id"])
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+ change_node(node, condition, init_graph)
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+ # Process goal conditions
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+ for condition in task.get("goal_conditions", []):
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+ node = (condition["node"]["name"], condition["node"]["id"])
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+ change_node(node, condition, goal_graph)
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+ # Process actions
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+ actions = []
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+ for action in task.get("actions", []):
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+ actions.append((action['action'], (action['node']["name"],action['node']["id"])))
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+ # Reset graph edges
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+ init_graph.remove_edges_from(list(office_graph.edges))
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+ goal_graph.remove_edges_from(list(office_graph.edges))
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+ add_edges(init_graph)
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+ add_edges(goal_graph)
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+
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+ entity = {
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+ "id": i,
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+ "name": name,
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+ "task": name,
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+ "init": init_graph,
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+ "goal": goal_graph,
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+ "actions": actions,
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+ }
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+ dataset.append(entity)
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+
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+ with open(OUT_FILENAME, "wb") as file:
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+ pickle.dump(dataset, file)
office/nodes.py ADDED
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+ OFFICES = [
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+ ('peters_office', 1), ('tobis_office', 1),
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+ ('nikos_office', 1), ('michaels_office', 1), ('aarons_office', 1), ('jasons_office', 1),
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+ ('filipes_office', 1), ('luis_office', 1), ('wills_office', 1),
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+ ('ajays_office', 1), ('chris_office', 1), ('lauriannes_office', 1), ('dimitys_office', 1)
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+ ]
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+
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+ ROOMS = [
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+ ('phd_bay', 1), ('phd_bay', 2), ('phd_bay', 3), ('phd_bay', 4),
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+ ('meeting_room', 1), ('meeting_room', 2), ('meeting_room', 3), ('meeting_room', 4),
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+ ('postdoc_bay', 1), ('postdoc_bay', 2), ('postdoc_bay', 3),
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+ ('printing_zone', 1), ('printing_zone', 2),
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+ ('admin', 1), ('lobby', 1), ('kitchen', 1), ('cafeteria', 1), ('presentation_lounge', 1),
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+ ('mobile_robotics_lab', 1), ('manipulation_lab', 1), ('agriculture_lab', 1),
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+ ('supplies_station', 1), ('robot_lounge', 1), ('robot_lounge', 2)
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+ ]
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+
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+ ASSETS = [
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+ (('fridge', 1), ('kitchen', 1), ['closed', 'clear'], ['open', 'close', 'put_inside'], []),
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+ (('dishwasher', 1), ('kitchen', 1), ['closed', 'off', 'clear'], ['open', 'close', 'turn_on', 'turn_off', 'put_on', 'put_inside'], []),
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+ (('coffee_machine', 1), ('kitchen', 1), ['off', 'clear'], ['turn_on', 'turn_off', 'put_inside'], []),
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+ (('microwave', 1), ('kitchen', 1), ['off', 'clear', 'closed'], ['open', 'close', 'turn_on', 'turn_off', 'put_on', 'put_inside'], []),
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+ (('kitchen_bench', 1), ('kitchen', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
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+ (('desk', 2), ('peters_office', 1), ['clear'], ['put_on'], []),
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+ (('cabinet', 2), ('peters_office', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
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+ (('desk', 35), ('postdoc_bay', 3), ['clear'], ['put_on'], []),
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+ (('desk', 36), ('postdoc_bay', 3), ['clear'], ['put_on'], []),
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+ (('table', 2), ('meeting_room', 4), ['clear'], ['put_on'], []),
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+ (('table', 5), ('meeting_room', 1), ['clear'], ['put_on'], []),
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+ (('table', 6), ('meeting_room', 3), ['clear'], ['put_on'], []),
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+ (('table', 1), ('meeting_room', 3), ['clear'], ['put_on'], []),
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+ (('chair', 3), ('meeting_room', 1), ['clear'], ['put_on'], []),
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+ (('chair', 4), ('meeting_room', 1), ['clear'], ['put_on'], []),
34
+ (('chair', 5), ('meeting_room', 1), ['clear'], ['put_on'], []),
35
+ (('chair', 2), ('meeting_room', 2), ['clear'], ['put_on'], []),
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+ (('desk', 32), ('postdoc_bay', 1), ['clear'], ['put_on'], []),
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+ (('desk', 38), ('tobis_office', 1), ['clear'], ['put_on'], []),
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+ (('printer', 2), ('printing_zone', 2), ['off', 'clear'], ['turn_on', 'turn_off'], []),
39
+ (('desk', 1), ('nikos_office', 1), ['clear'], ['put_on'], []),
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+ (('chair', 1), ('nikos_office', 1), ['clear'], ['put_on'], []),
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+ (('cabinet', 1), ('nikos_office', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
42
+ (('desk', 11), ('phd_bay', 1), ['clear'], ['put_on'], []),
43
+ (('desk', 8), ('phd_bay', 1), ['clear'], ['put_on'], []),
44
+ (('desk', 9), ('phd_bay', 1), ['clear'], ['put_on'], []),
45
+ (('desk', 10), ('phd_bay', 1), ['clear'], ['put_on'], []),
46
+ (('desk', 12), ('phd_bay', 1), ['clear'], ['put_on'], []),
47
+ (('desk', 7), ('phd_bay', 1), ['clear'], ['put_on'], []),
48
+ (('desk', 6), ('michaels_office', 1), ['clear'], ['put_on'], []),
49
+ (('wall', 1), ('michaels_office', 1), ['clear'], ['attach_to'], []),
50
+ (('cabinet', 6), ('michaels_office', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
51
+ (('table', 4), ('mobile_robotics_lab', 1), ['clear'], ['put_on'], []),
52
+ (('table', 3), ('manipulation_lab', 1), ['clear'], ['put_on'], []),
53
+ (('toolbox', 1), ('robot_lounge', 2), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
54
+ (('desk', 37), ('filipes_office', 1), ['clear'], ['put_on'], []),
55
+ (('desk', 4), ('wills_office', 1), ['clear'], ['put_on'], []),
56
+ (('cabinet', 4), ('wills_office', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
57
+ (('desk', 19), ('phd_bay', 3), ['clear'], ['put_on'], []),
58
+ (('desk', 20), ('phd_bay', 3), ['clear'], ['put_on'], []),
59
+ (('desk', 21), ('phd_bay', 3), ['clear'], ['put_on'], []),
60
+ (('desk', 22), ('phd_bay', 3), ['clear'], ['put_on'], []),
61
+ (('desk', 23), ('phd_bay', 3), ['clear'], ['put_on'], []),
62
+ (('desk', 24), ('phd_bay', 3), ['clear'], ['put_on'], []),
63
+ (('desk', 33), ('postdoc_bay', 2), ['clear'], ['put_on'], []),
64
+ (('desk', 34), ('postdoc_bay', 2), ['clear'], ['put_on'], []),
65
+ (('desk', 5), ('jasons_office', 1), ['clear'], ['put_on'], []),
66
+ (('desk', 3), ('dimitys_office', 1), ['clear'], ['put_on'], []),
67
+ (('K31X', 1), ('dimitys_office', 1), ['clear'], [], []),
68
+ (('desk', 13), ('phd_bay', 2), ['clear'], ['put_on'], []),
69
+ (('desk', 14), ('phd_bay', 2), ['clear'], ['put_on'], []),
70
+ (('desk', 15), ('phd_bay', 2), ['clear'], ['put_on'], []),
71
+ (('desk', 16), ('phd_bay', 2), ['clear'], ['put_on'], []),
72
+ (('desk', 17), ('phd_bay', 2), ['clear'], ['put_on'], []),
73
+ (('desk', 18), ('phd_bay', 2), ['clear'], ['put_on'], []),
74
+ (('desk', 25), ('phd_bay', 4), ['clear'], ['put_on'], []),
75
+ (('desk', 26), ('phd_bay', 4), ['clear'], ['put_on'], []),
76
+ (('desk', 27), ('phd_bay', 4), ['clear'], ['put_on'], []),
77
+ (('desk', 28), ('phd_bay', 4), ['clear'], ['put_on'], []),
78
+ (('desk', 29), ('phd_bay', 4), ['clear'], ['put_on'], []),
79
+ (('desk', 30), ('phd_bay', 4), ['clear'], ['put_on'], []),
80
+ (('cabinet', 3), ('dimitys_office', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
81
+ (('cabinet', 5), ('jasons_office', 1), ['open', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
82
+ (('shelf', 1), ('admin', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
83
+ (('produce_container', 1), ('agriculture_lab', 1), ['clear'], ['put_on', 'put_inside'], []),
84
+ (('lunch_table', 1), ('cafeteria', 1), ['clear'], ['put_on'], []),
85
+ (('drawer', 1), ('kitchen', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
86
+ (('recycling_bin', 1), ('kitchen', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
87
+ (('rubbish_bin', 1), ('kitchen', 1), ['closed', 'clear'], ['open', 'close', 'put_on', 'put_inside'], []),
88
+ (('cupboard', 1), ('supplies_station', 1), ['closed', 'clear'], ['open', 'close','put_on', 'put_inside'], []),
89
+ (('cupboard', 2), ('supplies_station', 1), ['closed', 'clear'], ['open', 'close','put_on','put_inside'], []),
90
+ (('floor', 1), ('lobby', 1), ['clear'], ['put_on'], []),
91
+ (('shelf', 2), ('lobby', 1), ['clear'], ['put_on'], [])
92
+ ]
93
+
94
+ # Objects (name, relation, related, [states], [affordances], [properties] )
95
+ OBJECTS = [
96
+ (('bowl', 1), 'inside_of', ('dishwasher', 1), ['clear'], ['pick_up'], ['blue']),
97
+ (('banana', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
98
+ (('J64M', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
99
+ (('chicken_kebab', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
100
+ (('noodles', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
101
+ (('salmon_bagel', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
102
+ (('greek_salad', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
103
+ (('tomato', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
104
+ (('cheese', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
105
+ (('carrot', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
106
+ (('bag', 1), 'ontop_of', ('floor',1), ['clear'], ['pick_up'], []),
107
+ (('cup', 1), 'inside_of', ('dishwasher', 1), ['clear'], ['pick_up'], []),
108
+ (('milk', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
109
+ (('coffee_beans', 1), 'inside_of', ('fridge', 1), ['clear'], ['pick_up'], []),
110
+ (('knife', 1), 'ontop_of', ('kitchen_bench',1), ['clear'], ['pick_up'], []),
111
+ (('fork', 1), 'ontop_of', ('kitchen_bench',1), ['clear'], ['pick_up'], []),
112
+ (('fork', 2), 'ontop_of', ('lunch_table',1), ['clear'], ['pick_up'], []),
113
+ (('knife', 2), 'ontop_of', ('lunch_table',1), ['clear'], ['pick_up'], []),
114
+ (('banana', 2), 'ontop_of', ('lunch_table',1), ['clear', 'ripe'], ['pick_up'], []),
115
+ (('plate', 1), 'ontop_of', ('lunch_table',1), ['dirty'], ['pick_up'], []),
116
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202
+ },
203
+ "relation": "ontop_of",
204
+ "related_to": {
205
+ "name": "printer",
206
+ "id": 2
207
+ },
208
+ "states": [
209
+ "clear"
210
+ ]
211
+ }
212
+ ],
213
+ "goal_conditions": [
214
+ {
215
+ "node": {
216
+ "name": "document",
217
+ "id": 1
218
+ },
219
+ "relation": "ontop_of",
220
+ "related_to": {
221
+ "name": "desk",
222
+ "id": 4
223
+ },
224
+ "states": [
225
+ "clear"
226
+ ]
227
+ }
228
+ ],
229
+ "actions": [
230
+ {
231
+ "action": "go_to",
232
+ "node": {
233
+ "name": "printing_zone",
234
+ "id": 2
235
+ }
236
+ },
237
+ {
238
+ "action": "pick_up",
239
+ "node": {
240
+ "name": "document",
241
+ "id": 1
242
+ }
243
+ },
244
+ {
245
+ "action": "go_to",
246
+ "node": {
247
+ "name": "wills_office",
248
+ "id": 1
249
+ }
250
+ },
251
+ {
252
+ "action": "put_on",
253
+ "node": {
254
+ "name": "desk",
255
+ "id": 4
256
+ }
257
+ }
258
+ ]
259
+ },
260
+ {
261
+ "name": "Get Peter a healthy snack from his cabinet. Put it on his desk.",
262
+ "important_objects": [
263
+ {
264
+ "name": "apple",
265
+ "id": 3
266
+ },
267
+ {
268
+ "name": "cabinet",
269
+ "id": 2
270
+ }
271
+ ],
272
+ "init_conditions": [
273
+ {
274
+ "node": {
275
+ "name": "apple",
276
+ "id": 3
277
+ },
278
+ "relation": "inside_of",
279
+ "related_to": {
280
+ "name": "cabinet",
281
+ "id": 2
282
+ },
283
+ "states": null
284
+ },
285
+ {
286
+ "node": {
287
+ "name": "cabinet",
288
+ "id": 2
289
+ },
290
+ "relation": null,
291
+ "related_to": null,
292
+ "states": [
293
+ "closed"
294
+ ]
295
+ }
296
+ ],
297
+ "goal_conditions": [
298
+ {
299
+ "node": {
300
+ "name": "apple",
301
+ "id": 3
302
+ },
303
+ "relation": "ontop_of",
304
+ "related_to": {
305
+ "name": "desk",
306
+ "id": 2
307
+ },
308
+ "states": null
309
+ }
310
+ ],
311
+ "actions": [
312
+ {
313
+ "action": "go_to",
314
+ "node": {
315
+ "name": "peters_office",
316
+ "id": 1
317
+ }
318
+ },
319
+ {
320
+ "action": "open",
321
+ "node": {
322
+ "name": "cabinet",
323
+ "id": 2
324
+ }
325
+ },
326
+ {
327
+ "action": "pick_up",
328
+ "node": {
329
+ "name": "apple",
330
+ "id": 3
331
+ }
332
+ },
333
+ {
334
+ "action": "close",
335
+ "node": {
336
+ "name": "cabinet",
337
+ "id": 2
338
+ }
339
+ },
340
+ {
341
+ "action": "put_on",
342
+ "node": {
343
+ "name": "desk",
344
+ "id": 2
345
+ }
346
+ }
347
+ ]
348
+ },
349
+ {
350
+ "name": "Hide one of Peters valuable belongings.",
351
+ "important_objects": [
352
+ {
353
+ "name": "phone",
354
+ "id": 1
355
+ },
356
+ {
357
+ "name": "cabinet",
358
+ "id": 2
359
+ }
360
+ ],
361
+ "init_conditions": [
362
+ {
363
+ "node": {
364
+ "name": "phone",
365
+ "id": 1
366
+ },
367
+ "relation": "ontop_of",
368
+ "related_to": {
369
+ "name": "desk",
370
+ "id": 2
371
+ },
372
+ "states": [
373
+ "clear"
374
+ ]
375
+ }
376
+ ],
377
+ "goal_conditions": [
378
+ {
379
+ "node": {
380
+ "name": "phone",
381
+ "id": 1
382
+ },
383
+ "relation": "inside_of",
384
+ "related_to": {
385
+ "name": "cabinet",
386
+ "id": 2
387
+ },
388
+ "states": null
389
+ },
390
+ {
391
+ "node": {
392
+ "name": "cabinet",
393
+ "id": 2
394
+ },
395
+ "relation": null,
396
+ "related_to": null,
397
+ "states": [
398
+ "closed"
399
+ ]
400
+ }
401
+ ],
402
+ "actions": [
403
+ {
404
+ "action": "go_to",
405
+ "node": {
406
+ "name": "peters_office",
407
+ "id": 1
408
+ }
409
+ },
410
+ {
411
+ "action": "pick_up",
412
+ "node": {
413
+ "name": "phone",
414
+ "id": 1
415
+ }
416
+ },
417
+ {
418
+ "action": "open",
419
+ "node": {
420
+ "name": "cabinet",
421
+ "id": 2
422
+ }
423
+ },
424
+ {
425
+ "action": "put_inside",
426
+ "node": {
427
+ "name": "cabinet",
428
+ "id": 2
429
+ }
430
+ },
431
+ {
432
+ "action": "close",
433
+ "node": {
434
+ "name": "cabinet",
435
+ "id": 2
436
+ }
437
+ }
438
+ ]
439
+ },
440
+ {
441
+ "name": "Bring something to wipe the dusty admin shelf. Put it on shelf.",
442
+ "important_objects": [
443
+ {
444
+ "name": "paper_towel",
445
+ "id": 1
446
+ },
447
+ {
448
+ "name": "shelf",
449
+ "id": 1
450
+ }
451
+ ],
452
+ "init_conditions": [
453
+ {
454
+ "node": {
455
+ "name": "paper_towel",
456
+ "id": 1
457
+ },
458
+ "relation": "inside_of",
459
+ "related_to": {
460
+ "name": "cupboard",
461
+ "id": 1
462
+ },
463
+ "states": null
464
+ }
465
+ ],
466
+ "goal_conditions": [
467
+ {
468
+ "node": {
469
+ "name": "paper_towel",
470
+ "id": 1
471
+ },
472
+ "relation": "ontop_of",
473
+ "related_to": {
474
+ "name": "shelf",
475
+ "id": 1
476
+ },
477
+ "states": null
478
+ }
479
+ ],
480
+ "actions": [
481
+ {
482
+ "action": "go_to",
483
+ "node": {
484
+ "name": "supplies_station",
485
+ "id": 1
486
+ }
487
+ },
488
+ {
489
+ "action": "open",
490
+ "node": {
491
+ "name": "cupboard",
492
+ "id": 1
493
+ }
494
+ },
495
+ {
496
+ "action": "pick_up",
497
+ "node": {
498
+ "name": "paper_towel",
499
+ "id": 1
500
+ }
501
+ },
502
+ {
503
+ "action": "close",
504
+ "node": {
505
+ "name": "cupboard",
506
+ "id": 1
507
+ }
508
+ },
509
+ {
510
+ "action": "go_to",
511
+ "node": {
512
+ "name": "admin",
513
+ "id": 1
514
+ }
515
+ },
516
+ {
517
+ "action": "put_on",
518
+ "node": {
519
+ "name": "shelf",
520
+ "id": 1
521
+ }
522
+ }
523
+ ]
524
+ },
525
+ {
526
+ "name": "There is coffee dripping on the floor. Stop it.",
527
+ "important_objects": [
528
+ {
529
+ "name": "coffee_machine",
530
+ "id": 1
531
+ }
532
+ ],
533
+ "init_conditions": [
534
+ {
535
+ "node": {
536
+ "name": "coffee_machine",
537
+ "id": 1
538
+ },
539
+ "relation": null,
540
+ "related_to": null,
541
+ "states": [
542
+ "on"
543
+ ]
544
+ }
545
+ ],
546
+ "goal_conditions": [
547
+ {
548
+ "node": {
549
+ "name": "coffee_machine",
550
+ "id": 1
551
+ },
552
+ "relation": null,
553
+ "related_to": null,
554
+ "states": [
555
+ "off"
556
+ ]
557
+ }
558
+ ],
559
+ "actions": [
560
+ {
561
+ "action": "go_to",
562
+ "node": {
563
+ "name": "kitchen",
564
+ "id": 1
565
+ }
566
+ },
567
+ {
568
+ "action": "turn_off",
569
+ "node": {
570
+ "name": "coffee_machine",
571
+ "id": 1
572
+ }
573
+ }
574
+ ]
575
+ },
576
+ {
577
+ "name": "Place Wills drone on his desk.",
578
+ "important_objects": [
579
+ {
580
+ "name": "drone",
581
+ "id": 2
582
+ }
583
+ ],
584
+ "init_conditions": [
585
+ {
586
+ "node": {
587
+ "name": "drone",
588
+ "id": 2
589
+ },
590
+ "relation": "inside_of",
591
+ "related_to": {
592
+ "name": "cabinet",
593
+ "id": 4
594
+ },
595
+ "states": [
596
+ "clear"
597
+ ]
598
+ }
599
+ ],
600
+ "goal_conditions": [
601
+ {
602
+ "node": {
603
+ "name": "drone",
604
+ "id": 2
605
+ },
606
+ "relation": "ontop_of",
607
+ "related_to": {
608
+ "name": "desk",
609
+ "id": 4
610
+ },
611
+ "states": [
612
+ "clear"
613
+ ]
614
+ }
615
+ ],
616
+ "actions": [
617
+ {
618
+ "action": "go_to",
619
+ "node": {
620
+ "name": "wills_office",
621
+ "id": 1
622
+ }
623
+ },
624
+ {
625
+ "action": "open",
626
+ "node": {
627
+ "name": "cabinet",
628
+ "id": 4
629
+ }
630
+ },
631
+ {
632
+ "action": "pick_up",
633
+ "node": {
634
+ "name": "drone",
635
+ "id": 2
636
+ }
637
+ },
638
+ {
639
+ "action": "close",
640
+ "node": {
641
+ "name": "cabinet",
642
+ "id": 4
643
+ }
644
+ },
645
+ {
646
+ "action": "put_on",
647
+ "node": {
648
+ "name": "desk",
649
+ "id": 4
650
+ }
651
+ }
652
+ ]
653
+ },
654
+ {
655
+ "name": "Move the monitor from Jasons office to Filipes.",
656
+ "important_objects": [
657
+ {
658
+ "name": "monitor",
659
+ "id": 1
660
+ }
661
+ ],
662
+ "init_conditions": null,
663
+ "goal_conditions": [
664
+ {
665
+ "node": {
666
+ "name": "monitor",
667
+ "id": 1
668
+ },
669
+ "relation": "ontop_of",
670
+ "related_to": {
671
+ "name": "desk",
672
+ "id": 37
673
+ },
674
+ "states": [
675
+ "clear"
676
+ ]
677
+ }
678
+ ],
679
+ "actions": [
680
+ {
681
+ "action": "go_to",
682
+ "node": {
683
+ "name": "jasons_office",
684
+ "id": 1
685
+ }
686
+ },
687
+ {
688
+ "action": "pick_up",
689
+ "node": {
690
+ "name": "monitor",
691
+ "id": 1
692
+ }
693
+ },
694
+ {
695
+ "action": "go_to",
696
+ "node": {
697
+ "name": "filipes_office",
698
+ "id": 1
699
+ }
700
+ },
701
+ {
702
+ "action": "put_on",
703
+ "node": {
704
+ "name": "desk",
705
+ "id": 37
706
+ }
707
+ }
708
+ ]
709
+ },
710
+ {
711
+ "name": "My parcel just got delivered! Locate it and place it on the table in the manipulation lab.",
712
+ "important_objects": [
713
+ {
714
+ "name": "parcel",
715
+ "id": 1
716
+ }
717
+ ],
718
+ "init_conditions": [
719
+ {
720
+ "node": {
721
+ "name": "parcel",
722
+ "id": 1
723
+ },
724
+ "relation": "ontop_of",
725
+ "related_to": {
726
+ "name": "floor",
727
+ "id": 1
728
+ },
729
+ "states": [
730
+ "clear"
731
+ ]
732
+ }
733
+ ],
734
+ "goal_conditions": [
735
+ {
736
+ "node": {
737
+ "name": "parcel",
738
+ "id": 1
739
+ },
740
+ "relation": "ontop_of",
741
+ "related_to": {
742
+ "name": "table",
743
+ "id": 3
744
+ },
745
+ "states": null
746
+ }
747
+ ],
748
+ "actions": [
749
+ {
750
+ "action": "go_to",
751
+ "node": {
752
+ "name": "lobby",
753
+ "id": 1
754
+ }
755
+ },
756
+ {
757
+ "action": "pick_up",
758
+ "node": {
759
+ "name": "parcel",
760
+ "id": 1
761
+ }
762
+ },
763
+ {
764
+ "action": "go_to",
765
+ "node": {
766
+ "name": "manipulation_lab",
767
+ "id": 1
768
+ }
769
+ },
770
+ {
771
+ "action": "put_on",
772
+ "node": {
773
+ "name": "table",
774
+ "id": 3
775
+ }
776
+ }
777
+ ]
778
+ },
779
+ {
780
+ "name": "Heat up the chicken kebab. I will turn off microwave when needed.",
781
+ "important_objects": [
782
+ {
783
+ "name": "chicken_kebab",
784
+ "id": 1
785
+ },
786
+ {
787
+ "name": "microwave",
788
+ "id": 1
789
+ }
790
+ ],
791
+ "init_conditions": [
792
+ {
793
+ "node": {
794
+ "name": "chicken_kebab",
795
+ "id": 1
796
+ },
797
+ "relation": "inside_of",
798
+ "related_to": {
799
+ "name": "fridge",
800
+ "id": 1
801
+ },
802
+ "states": null
803
+ }
804
+ ],
805
+ "goal_conditions": [
806
+ {
807
+ "node": {
808
+ "name": "chicken_kebab",
809
+ "id": 1
810
+ },
811
+ "relation": "inside_of",
812
+ "related_to": {
813
+ "name": "microwave",
814
+ "id": 1
815
+ },
816
+ "states": ["hot"]
817
+ },
818
+ {
819
+ "node": {
820
+ "name": "microwave",
821
+ "id": 1
822
+ },
823
+ "relation": null,
824
+ "related_to": null,
825
+ "states": [
826
+ "closed",
827
+ "on"
828
+ ]
829
+ }
830
+ ],
831
+ "actions": [
832
+ {
833
+ "action": "go_to",
834
+ "node": {
835
+ "name": "kitchen",
836
+ "id": 1
837
+ }
838
+ },
839
+ {
840
+ "action": "open",
841
+ "node": {
842
+ "name": "fridge",
843
+ "id": 1
844
+ }
845
+ },
846
+ {
847
+ "action": "pick_up",
848
+ "node": {
849
+ "name": "chicken_kebab",
850
+ "id": 1
851
+ }
852
+ },
853
+ {
854
+ "action": "close",
855
+ "node": {
856
+ "name": "fridge",
857
+ "id": 1
858
+ }
859
+ },
860
+ {
861
+ "action": "open",
862
+ "node": {
863
+ "name": "microwave",
864
+ "id": 1
865
+ }
866
+ },
867
+ {
868
+ "action": "put_inside",
869
+ "node": {
870
+ "name": "microwave",
871
+ "id": 1
872
+ }
873
+ },
874
+ {
875
+ "action": "close",
876
+ "node": {
877
+ "name": "microwave",
878
+ "id": 1
879
+ }
880
+ },
881
+ {
882
+ "action": "turn_on",
883
+ "node": {
884
+ "name": "microwave",
885
+ "id": 1
886
+ }
887
+ }
888
+ ]
889
+ },
890
+ {
891
+ "name": "Salmon is smelling in the kitchen. Dispose of it.",
892
+ "important_objects": [
893
+ {
894
+ "name": "salmon_bagel",
895
+ "id": 1
896
+ },
897
+ {
898
+ "name": "rubbish_bin",
899
+ "id": 1
900
+ }
901
+ ],
902
+ "init_conditions": null,
903
+ "goal_conditions": [
904
+ {
905
+ "node": {
906
+ "name": "salmon_bagel",
907
+ "id": 1
908
+ },
909
+ "relation": "inside_of",
910
+ "related_to": {
911
+ "name": "rubbish_bin",
912
+ "id": 1
913
+ },
914
+ "states": null
915
+ }
916
+ ],
917
+ "actions": [
918
+ {
919
+ "action": "go_to",
920
+ "node": {
921
+ "name": "kitchen",
922
+ "id": 1
923
+ }
924
+ },
925
+ {
926
+ "action": "open",
927
+ "node": {
928
+ "name": "fridge",
929
+ "id": 1
930
+ }
931
+ },
932
+ {
933
+ "action": "pick_up",
934
+ "node": {
935
+ "name": "salmon_bagel",
936
+ "id": 1
937
+ }
938
+ },
939
+ {
940
+ "action": "open",
941
+ "node": {
942
+ "name": "rubbish_bin",
943
+ "id": 1
944
+ }
945
+ },
946
+ {
947
+ "action": "put_inside",
948
+ "node": {
949
+ "name": "rubbish_bin",
950
+ "id": 1
951
+ }
952
+ },
953
+ {
954
+ "action": "close",
955
+ "node": {
956
+ "name": "rubbish_bin",
957
+ "id": 1
958
+ }
959
+ },
960
+ {
961
+ "action": "close",
962
+ "node": {
963
+ "name": "fridge",
964
+ "id": 1
965
+ }
966
+ }
967
+ ]
968
+ },
969
+ {
970
+ "name": "Throw what the agent is holding in the bin and get back into lab.",
971
+ "important_objects": [
972
+ {
973
+ "name": "rubbish_bin",
974
+ "id": 1
975
+ }
976
+ ],
977
+ "init_conditions": [
978
+ {
979
+ "node": {
980
+ "name": "banana_peel",
981
+ "id": 1
982
+ },
983
+ "relation": "inside_hand",
984
+ "related_to": {
985
+ "name": "agent",
986
+ "id": 1
987
+ },
988
+ "states": null
989
+ },
990
+ {
991
+ "node": {
992
+ "name": "agent",
993
+ "id": 1
994
+ },
995
+ "relation": null,
996
+ "related_to": null,
997
+ "holding": {
998
+ "name": "banana_peel",
999
+ "id": 1
1000
+ },
1001
+ "states": null
1002
+ }
1003
+ ],
1004
+ "goal_conditions": [
1005
+ {
1006
+ "node": {
1007
+ "name": "banana_peel",
1008
+ "id": 1
1009
+ },
1010
+ "relation": "inside_of",
1011
+ "related_to": {
1012
+ "name": "rubbish_bin",
1013
+ "id": 1
1014
+ },
1015
+ "states": null
1016
+ }
1017
+ ],
1018
+ "actions": [
1019
+ {
1020
+ "action": "go_to",
1021
+ "node": {
1022
+ "name": "kitchen",
1023
+ "id": 1
1024
+ }
1025
+ },
1026
+ {
1027
+ "action": "open",
1028
+ "node": {
1029
+ "name": "rubbish_bin",
1030
+ "id": 1
1031
+ }
1032
+ },
1033
+ {
1034
+ "action": "put_inside",
1035
+ "node": {
1036
+ "name": "rubbish_bin",
1037
+ "id": 1
1038
+ }
1039
+ },
1040
+ {
1041
+ "action": "close",
1042
+ "node": {
1043
+ "name": "rubbish_bin",
1044
+ "id": 1
1045
+ }
1046
+ },
1047
+ {
1048
+ "action": "go_to",
1049
+ "node": {
1050
+ "name": "mobile_robotics_lab",
1051
+ "id": 1
1052
+ }
1053
+ }
1054
+ ]
1055
+ },
1056
+ {
1057
+ "name": "Heat up the noodles from fridge, and place it on lunch table.",
1058
+ "important_objects": [
1059
+ {
1060
+ "name": "noodles",
1061
+ "id": 1
1062
+ },
1063
+ {
1064
+ "name": "fridge",
1065
+ "id": 1
1066
+ },
1067
+ {
1068
+ "name": "microwave",
1069
+ "id": 1
1070
+ }
1071
+ ],
1072
+ "init_conditions": null,
1073
+ "goal_conditions": [
1074
+ {
1075
+ "node": {
1076
+ "name": "noodles",
1077
+ "id": 1
1078
+ },
1079
+ "relation": "ontop_of",
1080
+ "related_to": {
1081
+ "name": "lunch_table",
1082
+ "id": 1
1083
+ },
1084
+ "states": [
1085
+ "hot"
1086
+ ]
1087
+ }
1088
+ ],
1089
+ "actions": [
1090
+ {
1091
+ "action": "go_to",
1092
+ "node": {
1093
+ "name": "kitchen",
1094
+ "id": 1
1095
+ }
1096
+ },
1097
+ {
1098
+ "action": "open",
1099
+ "node": {
1100
+ "name": "fridge",
1101
+ "id": 1
1102
+ }
1103
+ },
1104
+ {
1105
+ "action": "pick_up",
1106
+ "node": {
1107
+ "name": "noodles",
1108
+ "id": 1
1109
+ }
1110
+ },
1111
+ {
1112
+ "action": "close",
1113
+ "node": {
1114
+ "name": "fridge",
1115
+ "id": 1
1116
+ }
1117
+ },
1118
+ {
1119
+ "action": "open",
1120
+ "node": {
1121
+ "name": "microwave",
1122
+ "id": 1
1123
+ }
1124
+ },
1125
+ {
1126
+ "action": "put_inside",
1127
+ "node": {
1128
+ "name": "microwave",
1129
+ "id": 1
1130
+ }
1131
+ },
1132
+ {
1133
+ "action": "close",
1134
+ "node": {
1135
+ "name": "microwave",
1136
+ "id": 1
1137
+ }
1138
+ },
1139
+ {
1140
+ "action": "turn_on",
1141
+ "node": {
1142
+ "name": "microwave",
1143
+ "id": 1
1144
+ }
1145
+ },
1146
+ {
1147
+ "action": "turn_off",
1148
+ "node": {
1149
+ "name": "microwave",
1150
+ "id": 1
1151
+ }
1152
+ },
1153
+ {
1154
+ "action": "open",
1155
+ "node": {
1156
+ "name": "microwave",
1157
+ "id": 1
1158
+ }
1159
+ },
1160
+ {
1161
+ "action": "pick_up",
1162
+ "node": {
1163
+ "name": "noodles",
1164
+ "id": 1
1165
+ }
1166
+ },
1167
+ {
1168
+ "action": "close",
1169
+ "node": {
1170
+ "name": "microwave",
1171
+ "id": 1
1172
+ }
1173
+ },
1174
+ {
1175
+ "action": "go_to",
1176
+ "node": {
1177
+ "name": "cafeteria",
1178
+ "id": 1
1179
+ }
1180
+ },
1181
+ {
1182
+ "action": "put_on",
1183
+ "node": {
1184
+ "name": "lunch_table",
1185
+ "id": 1
1186
+ }
1187
+ }
1188
+ ]
1189
+ },
1190
+ {
1191
+ "name": "Throw the rotting fruit in Dimitrys office in the correct bin.",
1192
+ "important_objects": null,
1193
+ "init_conditions": null,
1194
+ "goal_conditions": [
1195
+ {
1196
+ "node": {
1197
+ "name": "apple",
1198
+ "id": 2
1199
+ },
1200
+ "relation": "inside_of",
1201
+ "related_to": {
1202
+ "name": "rubbish_bin",
1203
+ "id": 1
1204
+ },
1205
+ "states": null
1206
+ }
1207
+ ],
1208
+ "actions": [
1209
+ {
1210
+ "action": "go_to",
1211
+ "node": {
1212
+ "name": "dimitys_office",
1213
+ "id": 1
1214
+ }
1215
+ },
1216
+ {
1217
+ "action": "open",
1218
+ "node": {
1219
+ "name": "cabinet",
1220
+ "id": 3
1221
+ }
1222
+ },
1223
+ {
1224
+ "action": "pick_up",
1225
+ "node": {
1226
+ "name": "apple",
1227
+ "id": 2
1228
+ }
1229
+ },
1230
+ {
1231
+ "action": "close",
1232
+ "node": {
1233
+ "name": "cabinet",
1234
+ "id": 3
1235
+ }
1236
+ },
1237
+ {
1238
+ "action": "go_to",
1239
+ "node": {
1240
+ "name": "kitchen",
1241
+ "id": 1
1242
+ }
1243
+ },
1244
+ {
1245
+ "action": "open",
1246
+ "node": {
1247
+ "name": "rubbish_bin",
1248
+ "id": 1
1249
+ }
1250
+ },
1251
+ {
1252
+ "action": "put_inside",
1253
+ "node": {
1254
+ "name": "rubbish_bin",
1255
+ "id": 1
1256
+ }
1257
+ },
1258
+ {
1259
+ "action": "close",
1260
+ "node": {
1261
+ "name": "rubbish_bin",
1262
+ "id": 1
1263
+ }
1264
+ }
1265
+ ]
1266
+ },
1267
+ {
1268
+ "name": "Clean up lunch table. Place clutery in the drawer. And dirty plate into dishwasher.",
1269
+ "important_objects": [
1270
+ {
1271
+ "name": "plate",
1272
+ "id": 1
1273
+ },
1274
+ {
1275
+ "name": "knife",
1276
+ "id": 2
1277
+ },
1278
+ {
1279
+ "name": "fork",
1280
+ "id": 2
1281
+ },
1282
+ {
1283
+ "name": "dishwasher",
1284
+ "id": 1
1285
+ },
1286
+ {
1287
+ "name": "drawer",
1288
+ "id": 1
1289
+ }
1290
+ ],
1291
+ "init_conditions": null,
1292
+ "goal_conditions": [
1293
+ {
1294
+ "node": {
1295
+ "name": "plate",
1296
+ "id": 1
1297
+ },
1298
+ "relation": "inside_of",
1299
+ "related_to": {
1300
+ "name": "dishwasher",
1301
+ "id": 1
1302
+ },
1303
+ "states": null
1304
+ },
1305
+ {
1306
+ "node": {
1307
+ "name": "knife",
1308
+ "id": 1
1309
+ },
1310
+ "relation": "inside_of",
1311
+ "related_to": {
1312
+ "name": "drawer",
1313
+ "id": 1
1314
+ },
1315
+ "states": null
1316
+ },
1317
+ {
1318
+ "node": {
1319
+ "name": "knife",
1320
+ "id": 2
1321
+ },
1322
+ "relation": "inside_of",
1323
+ "related_to": {
1324
+ "name": "drawer",
1325
+ "id": 1
1326
+ },
1327
+ "states": null
1328
+ },
1329
+ {
1330
+ "node": {
1331
+ "name": "fork",
1332
+ "id": 1
1333
+ },
1334
+ "relation": "inside_of",
1335
+ "related_to": {
1336
+ "name": "drawer",
1337
+ "id": 1
1338
+ },
1339
+ "states": null
1340
+ },
1341
+ {
1342
+ "node": {
1343
+ "name": "fork",
1344
+ "id": 2
1345
+ },
1346
+ "relation": "inside_of",
1347
+ "related_to": {
1348
+ "name": "drawer",
1349
+ "id": 1
1350
+ },
1351
+ "states": null
1352
+ }
1353
+ ],
1354
+ "actions": [
1355
+ {
1356
+ "action": "go_to",
1357
+ "node": {
1358
+ "name": "kitchen",
1359
+ "id": 1
1360
+ }
1361
+ },
1362
+ {
1363
+ "action": "open",
1364
+ "node": {
1365
+ "name": "drawer",
1366
+ "id": 1
1367
+ }
1368
+ },
1369
+ {
1370
+ "action": "pick_up",
1371
+ "node": {
1372
+ "name": "knife",
1373
+ "id": 1
1374
+ }
1375
+ },
1376
+ {
1377
+ "action": "put_inside",
1378
+ "node": {
1379
+ "name": "drawer",
1380
+ "id": 1
1381
+ }
1382
+ },
1383
+ {
1384
+ "action": "pick_up",
1385
+ "node": {
1386
+ "name": "fork",
1387
+ "id": 1
1388
+ }
1389
+ },
1390
+ {
1391
+ "action": "put_inside",
1392
+ "node": {
1393
+ "name": "drawer",
1394
+ "id": 1
1395
+ }
1396
+ },
1397
+ {
1398
+ "action": "go_to",
1399
+ "node": {
1400
+ "name": "cafeteria",
1401
+ "id": 1
1402
+ }
1403
+ },
1404
+ {
1405
+ "action": "pick_up",
1406
+ "node": {
1407
+ "name": "fork",
1408
+ "id": 2
1409
+ }
1410
+ },
1411
+ {
1412
+ "action": "go_to",
1413
+ "node": {
1414
+ "name": "kitchen",
1415
+ "id": 1
1416
+ }
1417
+ },
1418
+ {
1419
+ "action": "put_inside",
1420
+ "node": {
1421
+ "name": "drawer",
1422
+ "id": 1
1423
+ }
1424
+ },
1425
+ {
1426
+ "action": "go_to",
1427
+ "node": {
1428
+ "name": "cafeteria",
1429
+ "id": 1
1430
+ }
1431
+ },
1432
+ {
1433
+ "action": "pick_up",
1434
+ "node": {
1435
+ "name": "knife",
1436
+ "id": 2
1437
+ }
1438
+ },
1439
+ {
1440
+ "action": "go_to",
1441
+ "node": {
1442
+ "name": "kitchen",
1443
+ "id": 1
1444
+ }
1445
+ },
1446
+ {
1447
+ "action": "put_inside",
1448
+ "node": {
1449
+ "name": "drawer",
1450
+ "id": 1
1451
+ }
1452
+ },
1453
+ {
1454
+ "action": "close",
1455
+ "node": {
1456
+ "name": "drawer",
1457
+ "id": 1
1458
+ }
1459
+ },
1460
+ {
1461
+ "action": "go_to",
1462
+ "node": {
1463
+ "name": "cafeteria",
1464
+ "id": 1
1465
+ }
1466
+ },
1467
+ {
1468
+ "action": "pick_up",
1469
+ "node": {
1470
+ "name": "plate",
1471
+ "id": 1
1472
+ }
1473
+ },
1474
+ {
1475
+ "action": "go_to",
1476
+ "node": {
1477
+ "name": "kitchen",
1478
+ "id": 1
1479
+ }
1480
+ },
1481
+ {
1482
+ "action": "open",
1483
+ "node": {
1484
+ "name": "dishwasher",
1485
+ "id": 1
1486
+ }
1487
+ },
1488
+ {
1489
+ "action": "put_inside",
1490
+ "node": {
1491
+ "name": "dishwasher",
1492
+ "id": 1
1493
+ }
1494
+ },
1495
+ {
1496
+ "action": "close",
1497
+ "node": {
1498
+ "name": "dishwasher",
1499
+ "id": 1
1500
+ }
1501
+ }
1502
+ ]
1503
+ },
1504
+ {
1505
+ "name": "Safely file away the freshly printed document in Wills cabinet, then place the undergraduate thesis on his desk.",
1506
+ "important_objects": [
1507
+ {
1508
+ "name": "document",
1509
+ "id": 1
1510
+ },
1511
+ {
1512
+ "name": "cabinet",
1513
+ "id": 4
1514
+ },
1515
+ {
1516
+ "name": "undergrad_thesis",
1517
+ "id": 1
1518
+ },
1519
+ {
1520
+ "name": "desk",
1521
+ "id": 4
1522
+ }
1523
+ ],
1524
+ "init_conditions": null,
1525
+ "goal_conditions": [
1526
+ {
1527
+ "node": {
1528
+ "name": "document",
1529
+ "id": 1
1530
+ },
1531
+ "relation": "inside_of",
1532
+ "related_to": {
1533
+ "name": "cabinet",
1534
+ "id": 4
1535
+ },
1536
+ "states": null
1537
+ },
1538
+ {
1539
+ "node": {
1540
+ "name": "cabinet",
1541
+ "id": 4
1542
+ },
1543
+ "relation": null,
1544
+ "related_to": null,
1545
+ "states": [
1546
+ "closed"
1547
+ ]
1548
+ },
1549
+ {
1550
+ "node": {
1551
+ "name": "undergrad_thesis",
1552
+ "id": 1
1553
+ },
1554
+ "relation": "ontop_of",
1555
+ "related_to": {
1556
+ "name": "desk",
1557
+ "id": 4
1558
+ },
1559
+ "states": null
1560
+ }
1561
+ ],
1562
+ "actions": [
1563
+ {
1564
+ "action": "go_to",
1565
+ "node": {
1566
+ "name": "printing_zone",
1567
+ "id": 2
1568
+ }
1569
+ },
1570
+ {
1571
+ "action": "pick_up",
1572
+ "node": {
1573
+ "name": "document",
1574
+ "id": 1
1575
+ }
1576
+ },
1577
+ {
1578
+ "action": "go_to",
1579
+ "node": {
1580
+ "name": "wills_office",
1581
+ "id": 1
1582
+ }
1583
+ },
1584
+ {
1585
+ "action": "open",
1586
+ "node": {
1587
+ "name": "cabinet",
1588
+ "id": 4
1589
+ }
1590
+ },
1591
+ {
1592
+ "action": "put_inside",
1593
+ "node": {
1594
+ "name": "cabinet",
1595
+ "id": 4
1596
+ }
1597
+ },
1598
+ {
1599
+ "action": "pick_up",
1600
+ "node": {
1601
+ "name": "undergrad_thesis",
1602
+ "id": 1
1603
+ }
1604
+ },
1605
+ {
1606
+ "action": "close",
1607
+ "node": {
1608
+ "name": "cabinet",
1609
+ "id": 4
1610
+ }
1611
+ },
1612
+ {
1613
+ "action": "put_on",
1614
+ "node": {
1615
+ "name": "desk",
1616
+ "id": 4
1617
+ }
1618
+ }
1619
+ ]
1620
+ },
1621
+ {
1622
+ "name": "Make a coffee for Niko in his coffee mug and set the mug on his desk.",
1623
+ "important_objects": [
1624
+ {
1625
+ "name": "coffee_mug",
1626
+ "id": 1
1627
+ },
1628
+ {
1629
+ "name": "coffee_machine",
1630
+ "id": 1
1631
+ },
1632
+ {
1633
+ "name": "desk",
1634
+ "id": 1
1635
+ }
1636
+ ],
1637
+ "init_conditions": null,
1638
+ "goal_conditions": [
1639
+ {
1640
+ "node": {
1641
+ "name": "coffee_mug",
1642
+ "id": 1
1643
+ },
1644
+ "relation": "ontop_of",
1645
+ "related_to": {
1646
+ "name": "desk",
1647
+ "id": 1
1648
+ },
1649
+ "states": [
1650
+ "filled_coffee"
1651
+ ]
1652
+ }
1653
+ ],
1654
+ "actions": [
1655
+ {
1656
+ "action": "go_to",
1657
+ "node": {
1658
+ "name": "nikos_office",
1659
+ "id": 1
1660
+ }
1661
+ },
1662
+ {
1663
+ "action": "pick_up",
1664
+ "node": {
1665
+ "name": "coffee_mug",
1666
+ "id": 1
1667
+ }
1668
+ },
1669
+ {
1670
+ "action": "go_to",
1671
+ "node": {
1672
+ "name": "kitchen",
1673
+ "id": 1
1674
+ }
1675
+ },
1676
+ {
1677
+ "action": "put_inside",
1678
+ "node": {
1679
+ "name": "coffee_machine",
1680
+ "id": 1
1681
+ }
1682
+ },
1683
+ {
1684
+ "action": "turn_on",
1685
+ "node": {
1686
+ "name": "coffee_machine",
1687
+ "id": 1
1688
+ }
1689
+ },
1690
+ {
1691
+ "action": "turn_off",
1692
+ "node": {
1693
+ "name": "coffee_machine",
1694
+ "id": 1
1695
+ }
1696
+ },
1697
+ {
1698
+ "action": "pick_up",
1699
+ "node": {
1700
+ "name": "coffee_mug",
1701
+ "id": 1
1702
+ }
1703
+ },
1704
+ {
1705
+ "action": "go_to",
1706
+ "node": {
1707
+ "name": "nikos_office",
1708
+ "id": 1
1709
+ }
1710
+ },
1711
+ {
1712
+ "action": "put_on",
1713
+ "node": {
1714
+ "name": "desk",
1715
+ "id": 1
1716
+ }
1717
+ }
1718
+ ]
1719
+ },
1720
+ {
1721
+ "name": "Correct the misplaced items in the wrong trash bins.",
1722
+ "important_objects": [
1723
+ {
1724
+ "name": "milk_carton",
1725
+ "id": 1
1726
+ },
1727
+ {
1728
+ "name": "orange_peel",
1729
+ "id": 1
1730
+ },
1731
+ {
1732
+ "name": "apple_core",
1733
+ "id": 1
1734
+ },
1735
+ {
1736
+ "name": "banana_peel",
1737
+ "id": 1
1738
+ },
1739
+ {
1740
+ "name": "plastic_bottle",
1741
+ "id": 1
1742
+ },
1743
+ {
1744
+ "name": "recycling_bin",
1745
+ "id": 1
1746
+ },
1747
+ {
1748
+ "name": "rubbish_bin",
1749
+ "id": 1
1750
+ }
1751
+ ],
1752
+ "init_conditions": null,
1753
+ "goal_conditions": [
1754
+ {
1755
+ "node": {
1756
+ "name": "milk_carton",
1757
+ "id": 1
1758
+ },
1759
+ "relation": "inside_of",
1760
+ "related_to": {
1761
+ "name": "recycling_bin",
1762
+ "id": 1
1763
+ },
1764
+ "states": null
1765
+ },
1766
+ {
1767
+ "node": {
1768
+ "name": "orange_peel",
1769
+ "id": 1
1770
+ },
1771
+ "relation": "inside_of",
1772
+ "related_to": {
1773
+ "name": "rubbish_bin",
1774
+ "id": 1
1775
+ },
1776
+ "states": null
1777
+ },
1778
+ {
1779
+ "node": {
1780
+ "name": "apple_core",
1781
+ "id": 1
1782
+ },
1783
+ "relation": "inside_of",
1784
+ "related_to": {
1785
+ "name": "rubbish_bin",
1786
+ "id": 1
1787
+ },
1788
+ "states": null
1789
+ },
1790
+ {
1791
+ "node": {
1792
+ "name": "banana_peel",
1793
+ "id": 1
1794
+ },
1795
+ "relation": "inside_of",
1796
+ "related_to": {
1797
+ "name": "rubbish_bin",
1798
+ "id": 1
1799
+ },
1800
+ "states": null
1801
+ },
1802
+ {
1803
+ "node": {
1804
+ "name": "plastic_bottle",
1805
+ "id": 1
1806
+ },
1807
+ "relation": "inside_of",
1808
+ "related_to": {
1809
+ "name": "recycling_bin",
1810
+ "id": 1
1811
+ },
1812
+ "states": null
1813
+ }
1814
+ ],
1815
+ "actions": [
1816
+ {
1817
+ "action": "go_to",
1818
+ "node": {
1819
+ "name": "kitchen",
1820
+ "id": 1
1821
+ }
1822
+ },
1823
+ {
1824
+ "action": "open",
1825
+ "node": {
1826
+ "name": "rubbish_bin",
1827
+ "id": 1
1828
+ }
1829
+ },
1830
+ {
1831
+ "action": "open",
1832
+ "node": {
1833
+ "name": "recycling_bin",
1834
+ "id": 1
1835
+ }
1836
+ },
1837
+ {
1838
+ "action": "pick_up",
1839
+ "node": {
1840
+ "name": "plastic_bottle",
1841
+ "id": 1
1842
+ }
1843
+ },
1844
+ {
1845
+ "action": "put_inside",
1846
+ "node": {
1847
+ "name": "recycling_bin",
1848
+ "id": 1
1849
+ }
1850
+ },
1851
+ {
1852
+ "action": "pick_up",
1853
+ "node": {
1854
+ "name": "orange_peel",
1855
+ "id": 1
1856
+ }
1857
+ },
1858
+ {
1859
+ "action": "put_inside",
1860
+ "node": {
1861
+ "name": "rubbish_bin",
1862
+ "id": 1
1863
+ }
1864
+ },
1865
+ {
1866
+ "action": "pick_up",
1867
+ "node": {
1868
+ "name": "apple_core",
1869
+ "id": 1
1870
+ }
1871
+ },
1872
+ {
1873
+ "action": "put_inside",
1874
+ "node": {
1875
+ "name": "rubbish_bin",
1876
+ "id": 1
1877
+ }
1878
+ },
1879
+ {
1880
+ "action": "close",
1881
+ "node": {
1882
+ "name": "rubbish_bin",
1883
+ "id": 1
1884
+ }
1885
+ },
1886
+ {
1887
+ "action": "close",
1888
+ "node": {
1889
+ "name": "recycling_bin",
1890
+ "id": 1
1891
+ }
1892
+ }
1893
+ ]
1894
+ },
1895
+ {
1896
+ "name": "Tobi spilt soda on his desk. Throw away the can and put on his table something to clean with.",
1897
+ "important_objects": [
1898
+ {
1899
+ "name": "pepsi",
1900
+ "id": 1
1901
+ },
1902
+ {
1903
+ "name": "rubbish_bin",
1904
+ "id": 1
1905
+ },
1906
+ {
1907
+ "name": "paper_towel",
1908
+ "id": 1
1909
+ },
1910
+ {
1911
+ "name": "cupboard",
1912
+ "id": 1
1913
+ }
1914
+ ],
1915
+ "init_conditions": null,
1916
+ "goal_conditions": [
1917
+ {
1918
+ "node": {
1919
+ "name": "pepsi",
1920
+ "id": 1
1921
+ },
1922
+ "relation": "inside_of",
1923
+ "related_to": {
1924
+ "name": "rubbish_bin",
1925
+ "id": 1
1926
+ },
1927
+ "states": null
1928
+ },
1929
+ {
1930
+ "node": {
1931
+ "name": "paper_towel",
1932
+ "id": 1
1933
+ },
1934
+ "relation": "ontop_of",
1935
+ "related_to": {
1936
+ "name": "desk",
1937
+ "id": 38
1938
+ },
1939
+ "states": null
1940
+ }
1941
+ ],
1942
+ "actions": [
1943
+ {
1944
+ "action": "go_to",
1945
+ "node": {
1946
+ "name": "tobis_office",
1947
+ "id": 1
1948
+ }
1949
+ },
1950
+ {
1951
+ "action": "pick_up",
1952
+ "node": {
1953
+ "name": "pepsi",
1954
+ "id": 1
1955
+ }
1956
+ },
1957
+ {
1958
+ "action": "go_to",
1959
+ "node": {
1960
+ "name": "kitchen",
1961
+ "id": 1
1962
+ }
1963
+ },
1964
+ {
1965
+ "action": "open",
1966
+ "node": {
1967
+ "name": "rubbish_bin",
1968
+ "id": 1
1969
+ }
1970
+ },
1971
+ {
1972
+ "action": "put_inside",
1973
+ "node": {
1974
+ "name": "rubbish_bin",
1975
+ "id": 1
1976
+ }
1977
+ },
1978
+ {
1979
+ "action": "close",
1980
+ "node": {
1981
+ "name": "rubbish_bin",
1982
+ "id": 1
1983
+ }
1984
+ },
1985
+ {
1986
+ "action": "go_to",
1987
+ "node": {
1988
+ "name": "supplies_station",
1989
+ "id": 1
1990
+ }
1991
+ },
1992
+ {
1993
+ "action": "open",
1994
+ "node": {
1995
+ "name": "cupboard",
1996
+ "id": 1
1997
+ }
1998
+ },
1999
+ {
2000
+ "action": "pick_up",
2001
+ "node": {
2002
+ "name": "paper_towel",
2003
+ "id": 1
2004
+ }
2005
+ },
2006
+ {
2007
+ "action": "close",
2008
+ "node": {
2009
+ "name": "cupboard",
2010
+ "id": 1
2011
+ }
2012
+ },
2013
+ {
2014
+ "action": "go_to",
2015
+ "node": {
2016
+ "name": "tobis_office",
2017
+ "id": 1
2018
+ }
2019
+ },
2020
+ {
2021
+ "action": "put_on",
2022
+ "node": {
2023
+ "name": "desk",
2024
+ "id": 38
2025
+ }
2026
+ }
2027
+ ]
2028
+ },
2029
+ {
2030
+ "name": "I want to make a sandwich with cheese tomato and kale. Place all the ingredients on the lunch table.",
2031
+ "important_objects": [
2032
+ {
2033
+ "name": "bread",
2034
+ "id": 1
2035
+ },
2036
+ {
2037
+ "name": "butter",
2038
+ "id": 1
2039
+ },
2040
+ {
2041
+ "name": "cheese",
2042
+ "id": 1
2043
+ },
2044
+ {
2045
+ "name": "tomato",
2046
+ "id": 1
2047
+ },
2048
+ {
2049
+ "name": "kale_leaves",
2050
+ "id": 2
2051
+ }
2052
+ ],
2053
+ "init_conditions": null,
2054
+ "goal_conditions": [
2055
+ {
2056
+ "node": {
2057
+ "name": "bread",
2058
+ "id": 1
2059
+ },
2060
+ "relation": "ontop_of",
2061
+ "related_to": {
2062
+ "name": "lunch_table",
2063
+ "id": 1
2064
+ },
2065
+ "states": null
2066
+ },
2067
+ {
2068
+ "node": {
2069
+ "name": "cheese",
2070
+ "id": 1
2071
+ },
2072
+ "relation": "ontop_of",
2073
+ "related_to": {
2074
+ "name": "lunch_table",
2075
+ "id": 1
2076
+ },
2077
+ "states": null
2078
+ },
2079
+ {
2080
+ "node": {
2081
+ "name": "tomato",
2082
+ "id": 1
2083
+ },
2084
+ "relation": "ontop_of",
2085
+ "related_to": {
2086
+ "name": "lunch_table",
2087
+ "id": 1
2088
+ },
2089
+ "states": null
2090
+ },
2091
+ {
2092
+ "node": {
2093
+ "name": "kale_leaves",
2094
+ "id": 2
2095
+ },
2096
+ "relation": "ontop_of",
2097
+ "related_to": {
2098
+ "name": "lunch_table",
2099
+ "id": 1
2100
+ },
2101
+ "states": null
2102
+ }
2103
+ ],
2104
+ "actions": [
2105
+ {
2106
+ "action": "go_to",
2107
+ "node": {
2108
+ "name": "kitchen",
2109
+ "id": 1
2110
+ }
2111
+ },
2112
+ {
2113
+ "action": "open",
2114
+ "node": {
2115
+ "name": "kitchen_bench",
2116
+ "id": 1
2117
+ }
2118
+ },
2119
+ {
2120
+ "action": "open",
2121
+ "node": {
2122
+ "name": "fridge",
2123
+ "id": 1
2124
+ }
2125
+ },
2126
+ {
2127
+ "action": "pick_up",
2128
+ "node": {
2129
+ "name": "bread",
2130
+ "id": 1
2131
+ }
2132
+ },
2133
+ {
2134
+ "action": "go_to",
2135
+ "node": {
2136
+ "name": "cafeteria",
2137
+ "id": 1
2138
+ }
2139
+ },
2140
+ {
2141
+ "action": "put_on",
2142
+ "node": {
2143
+ "name": "lunch_table",
2144
+ "id": 1
2145
+ }
2146
+ },
2147
+ {
2148
+ "action": "go_to",
2149
+ "node": {
2150
+ "name": "kitchen",
2151
+ "id": 1
2152
+ }
2153
+ },
2154
+ {
2155
+ "action": "pick_up",
2156
+ "node": {
2157
+ "name": "tomato",
2158
+ "id": 1
2159
+ }
2160
+ },
2161
+ {
2162
+ "action": "go_to",
2163
+ "node": {
2164
+ "name": "cafeteria",
2165
+ "id": 1
2166
+ }
2167
+ },
2168
+ {
2169
+ "action": "put_on",
2170
+ "node": {
2171
+ "name": "lunch_table",
2172
+ "id": 1
2173
+ }
2174
+ },
2175
+ {
2176
+ "action": "go_to",
2177
+ "node": {
2178
+ "name": "kitchen",
2179
+ "id": 1
2180
+ }
2181
+ },
2182
+ {
2183
+ "action": "pick_up",
2184
+ "node": {
2185
+ "name": "cheese",
2186
+ "id": 1
2187
+ }
2188
+ },
2189
+ {
2190
+ "action": "go_to",
2191
+ "node": {
2192
+ "name": "cafeteria",
2193
+ "id": 1
2194
+ }
2195
+ },
2196
+ {
2197
+ "action": "put_on",
2198
+ "node": {
2199
+ "name": "lunch_table",
2200
+ "id": 1
2201
+ }
2202
+ },
2203
+ {
2204
+ "action": "go_to",
2205
+ "node": {
2206
+ "name": "kitchen",
2207
+ "id": 1
2208
+ }
2209
+ },
2210
+ {
2211
+ "action": "pick_up",
2212
+ "node": {
2213
+ "name": "kale_leaves",
2214
+ "id": 2
2215
+ }
2216
+ },
2217
+ {
2218
+ "action": "close",
2219
+ "node": {
2220
+ "name": "kitchen_bench",
2221
+ "id": 1
2222
+ }
2223
+ },
2224
+ {
2225
+ "action": "close",
2226
+ "node": {
2227
+ "name": "fridge",
2228
+ "id": 1
2229
+ }
2230
+ },
2231
+ {
2232
+ "action": "go_to",
2233
+ "node": {
2234
+ "name": "cafeteria",
2235
+ "id": 1
2236
+ }
2237
+ },
2238
+ {
2239
+ "action": "put_on",
2240
+ "node": {
2241
+ "name": "lunch_table",
2242
+ "id": 1
2243
+ }
2244
+ }
2245
+ ]
2246
+ },
2247
+ {
2248
+ "name": "Prepare buiscuit water and orange juice on table in meeting room with board games.",
2249
+ "important_objects": [
2250
+ {
2251
+ "name": "bottled_water",
2252
+ "id": 1
2253
+ },
2254
+ {
2255
+ "name": "bottled_water",
2256
+ "id": 2
2257
+ },
2258
+ {
2259
+ "name": "bottled_water",
2260
+ "id": 3
2261
+ },
2262
+ {
2263
+ "name": "bottled_water",
2264
+ "id": 4
2265
+ },
2266
+ {
2267
+ "name": "bottled_water",
2268
+ "id": 5
2269
+ },
2270
+ {
2271
+ "name": "orange_juice",
2272
+ "id": 1
2273
+ },
2274
+ {
2275
+ "name": "biscuits",
2276
+ "id": 1
2277
+ }
2278
+ ],
2279
+ "init_conditions": null,
2280
+ "goal_conditions": [
2281
+ {
2282
+ "node": {
2283
+ "name": "bottled_water",
2284
+ "id": 1
2285
+ },
2286
+ "relation": "ontop_of",
2287
+ "related_to": {
2288
+ "name": "table",
2289
+ "id": 2
2290
+ },
2291
+ "states": null
2292
+ },
2293
+ {
2294
+ "node": {
2295
+ "name": "bottled_water",
2296
+ "id": 2
2297
+ },
2298
+ "relation": "ontop_of",
2299
+ "related_to": {
2300
+ "name": "table",
2301
+ "id": 2
2302
+ },
2303
+ "states": null
2304
+ },
2305
+ {
2306
+ "node": {
2307
+ "name": "bottled_water",
2308
+ "id": 3
2309
+ },
2310
+ "relation": "ontop_of",
2311
+ "related_to": {
2312
+ "name": "table",
2313
+ "id": 2
2314
+ },
2315
+ "states": null
2316
+ },
2317
+ {
2318
+ "node": {
2319
+ "name": "bottled_water",
2320
+ "id": 4
2321
+ },
2322
+ "relation": "ontop_of",
2323
+ "related_to": {
2324
+ "name": "table",
2325
+ "id": 2
2326
+ },
2327
+ "states": null
2328
+ },
2329
+ {
2330
+ "node": {
2331
+ "name": "bottled_water",
2332
+ "id": 5
2333
+ },
2334
+ "relation": "ontop_of",
2335
+ "related_to": {
2336
+ "name": "table",
2337
+ "id": 2
2338
+ },
2339
+ "states": null
2340
+ },
2341
+ {
2342
+ "node": {
2343
+ "name": "orange_juice",
2344
+ "id": 1
2345
+ },
2346
+ "relation": "ontop_of",
2347
+ "related_to": {
2348
+ "name": "table",
2349
+ "id": 2
2350
+ },
2351
+ "states": null
2352
+ },
2353
+ {
2354
+ "node": {
2355
+ "name": "biscuits",
2356
+ "id": 1
2357
+ },
2358
+ "relation": "ontop_of",
2359
+ "related_to": {
2360
+ "name": "table",
2361
+ "id": 2
2362
+ },
2363
+ "states": null
2364
+ }
2365
+ ],
2366
+ "actions": [
2367
+ {
2368
+ "action": "go_to",
2369
+ "node": {
2370
+ "name": "supplies_station",
2371
+ "id": 1
2372
+ }
2373
+ },
2374
+ {
2375
+ "action": "open",
2376
+ "node": {
2377
+ "name": "cupboard",
2378
+ "id": 1
2379
+ }
2380
+ },
2381
+ {
2382
+ "action": "open",
2383
+ "node": {
2384
+ "name": "cupboard",
2385
+ "id": 2
2386
+ }
2387
+ },
2388
+ {
2389
+ "action": "pick_up",
2390
+ "node": {
2391
+ "name": "biscuits",
2392
+ "id": 1
2393
+ }
2394
+ },
2395
+ {
2396
+ "action": "go_to",
2397
+ "node": {
2398
+ "name": "meeting_room",
2399
+ "id": 4
2400
+ }
2401
+ },
2402
+ {
2403
+ "action": "put_on",
2404
+ "node": {
2405
+ "name": "table",
2406
+ "id": 2
2407
+ }
2408
+ },
2409
+ {
2410
+ "action": "go_to",
2411
+ "node": {
2412
+ "name": "supplies_station",
2413
+ "id": 1
2414
+ }
2415
+ },
2416
+ {
2417
+ "action": "pick_up",
2418
+ "node": {
2419
+ "name": "orange_juice",
2420
+ "id": 1
2421
+ }
2422
+ },
2423
+ {
2424
+ "action": "go_to",
2425
+ "node": {
2426
+ "name": "meeting_room",
2427
+ "id": 4
2428
+ }
2429
+ },
2430
+ {
2431
+ "action": "put_on",
2432
+ "node": {
2433
+ "name": "table",
2434
+ "id": 2
2435
+ }
2436
+ },
2437
+ {
2438
+ "action": "go_to",
2439
+ "node": {
2440
+ "name": "supplies_station",
2441
+ "id": 1
2442
+ }
2443
+ },
2444
+ {
2445
+ "action": "pick_up",
2446
+ "node": {
2447
+ "name": "bottled_water",
2448
+ "id": 1
2449
+ }
2450
+ },
2451
+ {
2452
+ "action": "go_to",
2453
+ "node": {
2454
+ "name": "meeting_room",
2455
+ "id": 4
2456
+ }
2457
+ },
2458
+ {
2459
+ "action": "put_on",
2460
+ "node": {
2461
+ "name": "table",
2462
+ "id": 2
2463
+ }
2464
+ },
2465
+ {
2466
+ "action": "go_to",
2467
+ "node": {
2468
+ "name": "supplies_station",
2469
+ "id": 1
2470
+ }
2471
+ },
2472
+ {
2473
+ "action": "pick_up",
2474
+ "node": {
2475
+ "name": "bottled_water",
2476
+ "id": 2
2477
+ }
2478
+ },
2479
+ {
2480
+ "action": "go_to",
2481
+ "node": {
2482
+ "name": "meeting_room",
2483
+ "id": 4
2484
+ }
2485
+ },
2486
+ {
2487
+ "action": "put_on",
2488
+ "node": {
2489
+ "name": "table",
2490
+ "id": 2
2491
+ }
2492
+ },
2493
+ {
2494
+ "action": "go_to",
2495
+ "node": {
2496
+ "name": "supplies_station",
2497
+ "id": 1
2498
+ }
2499
+ },
2500
+ {
2501
+ "action": "pick_up",
2502
+ "node": {
2503
+ "name": "bottled_water",
2504
+ "id": 3
2505
+ }
2506
+ },
2507
+ {
2508
+ "action": "go_to",
2509
+ "node": {
2510
+ "name": "meeting_room",
2511
+ "id": 4
2512
+ }
2513
+ },
2514
+ {
2515
+ "action": "put_on",
2516
+ "node": {
2517
+ "name": "table",
2518
+ "id": 2
2519
+ }
2520
+ },
2521
+ {
2522
+ "action": "go_to",
2523
+ "node": {
2524
+ "name": "supplies_station",
2525
+ "id": 1
2526
+ }
2527
+ },
2528
+ {
2529
+ "action": "pick_up",
2530
+ "node": {
2531
+ "name": "bottled_water",
2532
+ "id": 4
2533
+ }
2534
+ },
2535
+ {
2536
+ "action": "go_to",
2537
+ "node": {
2538
+ "name": "meeting_room",
2539
+ "id": 4
2540
+ }
2541
+ },
2542
+ {
2543
+ "action": "put_on",
2544
+ "node": {
2545
+ "name": "table",
2546
+ "id": 2
2547
+ }
2548
+ },
2549
+ {
2550
+ "action": "go_to",
2551
+ "node": {
2552
+ "name": "supplies_station",
2553
+ "id": 1
2554
+ }
2555
+ },
2556
+ {
2557
+ "action": "pick_up",
2558
+ "node": {
2559
+ "name": "bottled_water",
2560
+ "id": 5
2561
+ }
2562
+ },
2563
+ {
2564
+ "action": "close",
2565
+ "node": {
2566
+ "name": "cupboard",
2567
+ "id": 1
2568
+ }
2569
+ },
2570
+ {
2571
+ "action": "close",
2572
+ "node": {
2573
+ "name": "cupboard",
2574
+ "id": 2
2575
+ }
2576
+ },
2577
+ {
2578
+ "action": "go_to",
2579
+ "node": {
2580
+ "name": "meeting_room",
2581
+ "id": 4
2582
+ }
2583
+ },
2584
+ {
2585
+ "action": "put_on",
2586
+ "node": {
2587
+ "name": "table",
2588
+ "id": 2
2589
+ }
2590
+ }
2591
+ ]
2592
+ },
2593
+ {
2594
+ "name": "Provide each seated attendee in Meeting Room 1 with a single bottle of water. Put water bottles on table.",
2595
+ "important_objects": [
2596
+ {
2597
+ "name": "bottled_water",
2598
+ "id": 1
2599
+ },
2600
+ {
2601
+ "name": "bottled_water",
2602
+ "id": 2
2603
+ },
2604
+ {
2605
+ "name": "bottled_water",
2606
+ "id": 3
2607
+ },
2608
+ {
2609
+ "name": "bottled_water",
2610
+ "id": 4
2611
+ },
2612
+ {
2613
+ "name": "bottled_water",
2614
+ "id": 5
2615
+ },
2616
+ {
2617
+ "name": "chair",
2618
+ "id": 3
2619
+ },
2620
+ {
2621
+ "name": "chair",
2622
+ "id": 4
2623
+ },
2624
+ {
2625
+ "name": "chair",
2626
+ "id": 5
2627
+ }
2628
+ ],
2629
+ "init_conditions": null,
2630
+ "goal_conditions": [
2631
+ {
2632
+ "node": {
2633
+ "name": "bottled_water",
2634
+ "id": 1
2635
+ },
2636
+ "relation": "ontop_of",
2637
+ "related_to": {
2638
+ "name": "table",
2639
+ "id": 5
2640
+ },
2641
+ "states": null
2642
+ },
2643
+ {
2644
+ "node": {
2645
+ "name": "bottled_water",
2646
+ "id": 2
2647
+ },
2648
+ "relation": "ontop_of",
2649
+ "related_to": {
2650
+ "name": "table",
2651
+ "id": 5
2652
+ },
2653
+ "states": null
2654
+ },
2655
+ {
2656
+ "node": {
2657
+ "name": "bottled_water",
2658
+ "id": 3
2659
+ },
2660
+ "relation": "ontop_of",
2661
+ "related_to": {
2662
+ "name": "table",
2663
+ "id": 5
2664
+ },
2665
+ "states": null
2666
+ }
2667
+ ],
2668
+ "actions": [
2669
+ {
2670
+ "action": "go_to",
2671
+ "node": {
2672
+ "name": "supplies_station",
2673
+ "id": 1
2674
+ }
2675
+ },
2676
+ {
2677
+ "action": "open",
2678
+ "node": {
2679
+ "name": "cupboard",
2680
+ "id": 2
2681
+ }
2682
+ },
2683
+ {
2684
+ "action": "pick_up",
2685
+ "node": {
2686
+ "name": "bottled_water",
2687
+ "id": 1
2688
+ }
2689
+ },
2690
+ {
2691
+ "action": "go_to",
2692
+ "node": {
2693
+ "name": "meeting_room",
2694
+ "id": 1
2695
+ }
2696
+ },
2697
+ {
2698
+ "action": "put_on",
2699
+ "node": {
2700
+ "name": "table",
2701
+ "id": 5
2702
+ }
2703
+ },
2704
+ {
2705
+ "action": "go_to",
2706
+ "node": {
2707
+ "name": "supplies_station",
2708
+ "id": 1
2709
+ }
2710
+ },
2711
+ {
2712
+ "action": "pick_up",
2713
+ "node": {
2714
+ "name": "bottled_water",
2715
+ "id": 2
2716
+ }
2717
+ },
2718
+ {
2719
+ "action": "go_to",
2720
+ "node": {
2721
+ "name": "meeting_room",
2722
+ "id": 1
2723
+ }
2724
+ },
2725
+ {
2726
+ "action": "put_on",
2727
+ "node": {
2728
+ "name": "table",
2729
+ "id": 5
2730
+ }
2731
+ },
2732
+ {
2733
+ "action": "go_to",
2734
+ "node": {
2735
+ "name": "supplies_station",
2736
+ "id": 1
2737
+ }
2738
+ },
2739
+ {
2740
+ "action": "pick_up",
2741
+ "node": {
2742
+ "name": "bottled_water",
2743
+ "id": 3
2744
+ }
2745
+ },
2746
+ {
2747
+ "action": "close",
2748
+ "node": {
2749
+ "name": "cupboard",
2750
+ "id": 2
2751
+ }
2752
+ },
2753
+ {
2754
+ "action": "go_to",
2755
+ "node": {
2756
+ "name": "meeting_room",
2757
+ "id": 1
2758
+ }
2759
+ },
2760
+ {
2761
+ "action": "put_on",
2762
+ "node": {
2763
+ "name": "table",
2764
+ "id": 5
2765
+ }
2766
+ }
2767
+ ]
2768
+ },
2769
+ {
2770
+ "name": "Empty the dishwasher. Place clutery in drawer and other inside bench.",
2771
+ "important_objects": [
2772
+ {
2773
+ "name": "dishwasher",
2774
+ "id": 1
2775
+ },
2776
+ {
2777
+ "name": "plate",
2778
+ "id": 2
2779
+ },
2780
+ {
2781
+ "name": "spoon",
2782
+ "id": 1
2783
+ },
2784
+ {
2785
+ "name": "bowl",
2786
+ "id": 1
2787
+ },
2788
+ {
2789
+ "name": "cup",
2790
+ "id": 1
2791
+ },
2792
+ {
2793
+ "name": "drawer",
2794
+ "id": 1
2795
+ },
2796
+ {
2797
+ "name": "kitchen_bench",
2798
+ "id": 1
2799
+ },
2800
+ {
2801
+ "name": "table",
2802
+ "id": 2
2803
+ }
2804
+ ],
2805
+ "init_conditions": null,
2806
+ "goal_conditions": [
2807
+ {
2808
+ "node": {
2809
+ "name": "plate",
2810
+ "id": 2
2811
+ },
2812
+ "relation": "inside_of",
2813
+ "related_to": {
2814
+ "name": "kitchen_bench",
2815
+ "id": 1
2816
+ },
2817
+ "states": null
2818
+ },
2819
+ {
2820
+ "node": {
2821
+ "name": "spoon",
2822
+ "id": 1
2823
+ },
2824
+ "relation": "inside_of",
2825
+ "related_to": {
2826
+ "name": "drawer",
2827
+ "id": 1
2828
+ },
2829
+ "states": null
2830
+ },
2831
+ {
2832
+ "node": {
2833
+ "name": "cup",
2834
+ "id": 1
2835
+ },
2836
+ "relation": "inside_of",
2837
+ "related_to": {
2838
+ "name": "kitchen_bench",
2839
+ "id": 1
2840
+ },
2841
+ "states": null
2842
+ }
2843
+ ],
2844
+ "actions": [
2845
+ {
2846
+ "action": "go_to",
2847
+ "node": {
2848
+ "name": "kitchen",
2849
+ "id": 1
2850
+ }
2851
+ },
2852
+ {
2853
+ "action": "open",
2854
+ "node": {
2855
+ "name": "dishwasher",
2856
+ "id": 1
2857
+ }
2858
+ },
2859
+ {
2860
+ "action": "pick_up",
2861
+ "node": {
2862
+ "name": "spoon",
2863
+ "id": 1
2864
+ }
2865
+ },
2866
+ {
2867
+ "action": "open",
2868
+ "node": {
2869
+ "name": "drawer",
2870
+ "id": 1
2871
+ }
2872
+ },
2873
+ {
2874
+ "action": "open",
2875
+ "node": {
2876
+ "name": "kitchen_bench",
2877
+ "id": 1
2878
+ }
2879
+ },
2880
+ {
2881
+ "action": "put_inside",
2882
+ "node": {
2883
+ "name": "drawer",
2884
+ "id": 1
2885
+ }
2886
+ },
2887
+ {
2888
+ "action": "close",
2889
+ "node": {
2890
+ "name": "drawer",
2891
+ "id": 1
2892
+ }
2893
+ },
2894
+ {
2895
+ "action": "pick_up",
2896
+ "node": {
2897
+ "name": "bowl",
2898
+ "id": 1
2899
+ }
2900
+ },
2901
+ {
2902
+ "action": "put_on",
2903
+ "node": {
2904
+ "name": "kitchen_bench",
2905
+ "id": 1
2906
+ }
2907
+ },
2908
+ {
2909
+ "action": "pick_up",
2910
+ "node": {
2911
+ "name": "cup",
2912
+ "id": 1
2913
+ }
2914
+ },
2915
+ {
2916
+ "action": "put_inside",
2917
+ "node": {
2918
+ "name": "kitchen_bench",
2919
+ "id": 1
2920
+ }
2921
+ },
2922
+ {
2923
+ "action": "pick_up",
2924
+ "node": {
2925
+ "name": "plate",
2926
+ "id": 2
2927
+ }
2928
+ },
2929
+ {
2930
+ "action": "put_inside",
2931
+ "node": {
2932
+ "name": "kitchen_bench",
2933
+ "id": 1
2934
+ }
2935
+ },
2936
+ {
2937
+ "action": "close",
2938
+ "node": {
2939
+ "name": "kitchen_bench",
2940
+ "id": 1
2941
+ }
2942
+ },
2943
+ {
2944
+ "action": "close",
2945
+ "node": {
2946
+ "name": "dishwasher",
2947
+ "id": 1
2948
+ }
2949
+ }
2950
+ ]
2951
+ },
2952
+ {
2953
+ "name": "Locate all 6 complimentary t-shirts given to the PhD students and place them on the shelf in admin.",
2954
+ "important_objects": [
2955
+ {
2956
+ "name": "complimentary_tshirt",
2957
+ "id": 1
2958
+ },
2959
+ {
2960
+ "name": "complimentary_tshirt",
2961
+ "id": 2
2962
+ },
2963
+ {
2964
+ "name": "complimentary_tshirt",
2965
+ "id": 3
2966
+ },
2967
+ {
2968
+ "name": "complimentary_tshirt",
2969
+ "id": 4
2970
+ },
2971
+ {
2972
+ "name": "complimentary_tshirt",
2973
+ "id": 5
2974
+ },
2975
+ {
2976
+ "name": "complimentary_tshirt",
2977
+ "id": 6
2978
+ },
2979
+ {
2980
+ "name": "shelf",
2981
+ "id": 1
2982
+ }
2983
+ ],
2984
+ "init_conditions": null,
2985
+ "goal_conditions": [
2986
+ {
2987
+ "node": {
2988
+ "name": "complimentary_tshirt",
2989
+ "id": 1
2990
+ },
2991
+ "relation": "ontop_of",
2992
+ "related_to": {
2993
+ "name": "shelf",
2994
+ "id": 1
2995
+ },
2996
+ "states": null
2997
+ },
2998
+ {
2999
+ "node": {
3000
+ "name": "complimentary_tshirt",
3001
+ "id": 2
3002
+ },
3003
+ "relation": "ontop_of",
3004
+ "related_to": {
3005
+ "name": "shelf",
3006
+ "id": 1
3007
+ },
3008
+ "states": null
3009
+ },
3010
+ {
3011
+ "node": {
3012
+ "name": "complimentary_tshirt",
3013
+ "id": 3
3014
+ },
3015
+ "relation": "ontop_of",
3016
+ "related_to": {
3017
+ "name": "shelf",
3018
+ "id": 1
3019
+ },
3020
+ "states": null
3021
+ },
3022
+ {
3023
+ "node": {
3024
+ "name": "complimentary_tshirt",
3025
+ "id": 4
3026
+ },
3027
+ "relation": "ontop_of",
3028
+ "related_to": {
3029
+ "name": "shelf",
3030
+ "id": 1
3031
+ },
3032
+ "states": null
3033
+ },
3034
+ {
3035
+ "node": {
3036
+ "name": "complimentary_tshirt",
3037
+ "id": 5
3038
+ },
3039
+ "relation": "ontop_of",
3040
+ "related_to": {
3041
+ "name": "shelf",
3042
+ "id": 1
3043
+ },
3044
+ "states": null
3045
+ },
3046
+ {
3047
+ "node": {
3048
+ "name": "complimentary_tshirt",
3049
+ "id": 6
3050
+ },
3051
+ "relation": "ontop_of",
3052
+ "related_to": {
3053
+ "name": "shelf",
3054
+ "id": 1
3055
+ },
3056
+ "states": null
3057
+ }
3058
+ ],
3059
+ "actions": [
3060
+ {
3061
+ "action": "go_to",
3062
+ "node": {
3063
+ "name": "phd_bay",
3064
+ "id": 1
3065
+ }
3066
+ },
3067
+ {
3068
+ "action": "pick_up",
3069
+ "node": {
3070
+ "name": "complimentary_tshirt",
3071
+ "id": 1
3072
+ }
3073
+ },
3074
+ {
3075
+ "action": "go_to",
3076
+ "node": {
3077
+ "name": "admin",
3078
+ "id": 1
3079
+ }
3080
+ },
3081
+ {
3082
+ "action": "put_on",
3083
+ "node": {
3084
+ "name": "shelf",
3085
+ "id": 1
3086
+ }
3087
+ },
3088
+ {
3089
+ "action": "go_to",
3090
+ "node": {
3091
+ "name": "phd_bay",
3092
+ "id": 1
3093
+ }
3094
+ },
3095
+ {
3096
+ "action": "pick_up",
3097
+ "node": {
3098
+ "name": "complimentary_tshirt",
3099
+ "id": 2
3100
+ }
3101
+ },
3102
+ {
3103
+ "action": "go_to",
3104
+ "node": {
3105
+ "name": "admin",
3106
+ "id": 1
3107
+ }
3108
+ },
3109
+ {
3110
+ "action": "put_on",
3111
+ "node": {
3112
+ "name": "shelf",
3113
+ "id": 1
3114
+ }
3115
+ },
3116
+ {
3117
+ "action": "go_to",
3118
+ "node": {
3119
+ "name": "phd_bay",
3120
+ "id": 2
3121
+ }
3122
+ },
3123
+ {
3124
+ "action": "pick_up",
3125
+ "node": {
3126
+ "name": "complimentary_tshirt",
3127
+ "id": 3
3128
+ }
3129
+ },
3130
+ {
3131
+ "action": "go_to",
3132
+ "node": {
3133
+ "name": "admin",
3134
+ "id": 1
3135
+ }
3136
+ },
3137
+ {
3138
+ "action": "put_on",
3139
+ "node": {
3140
+ "name": "shelf",
3141
+ "id": 1
3142
+ }
3143
+ },
3144
+ {
3145
+ "action": "go_to",
3146
+ "node": {
3147
+ "name": "phd_bay",
3148
+ "id": 2
3149
+ }
3150
+ },
3151
+ {
3152
+ "action": "pick_up",
3153
+ "node": {
3154
+ "name": "complimentary_tshirt",
3155
+ "id": 4
3156
+ }
3157
+ },
3158
+ {
3159
+ "action": "go_to",
3160
+ "node": {
3161
+ "name": "admin",
3162
+ "id": 1
3163
+ }
3164
+ },
3165
+ {
3166
+ "action": "put_on",
3167
+ "node": {
3168
+ "name": "shelf",
3169
+ "id": 1
3170
+ }
3171
+ },
3172
+ {
3173
+ "action": "go_to",
3174
+ "node": {
3175
+ "name": "phd_bay",
3176
+ "id": 4
3177
+ }
3178
+ },
3179
+ {
3180
+ "action": "pick_up",
3181
+ "node": {
3182
+ "name": "complimentary_tshirt",
3183
+ "id": 5
3184
+ }
3185
+ },
3186
+ {
3187
+ "action": "go_to",
3188
+ "node": {
3189
+ "name": "admin",
3190
+ "id": 1
3191
+ }
3192
+ },
3193
+ {
3194
+ "action": "put_on",
3195
+ "node": {
3196
+ "name": "shelf",
3197
+ "id": 1
3198
+ }
3199
+ },
3200
+ {
3201
+ "action": "go_to",
3202
+ "node": {
3203
+ "name": "phd_bay",
3204
+ "id": 2
3205
+ }
3206
+ },
3207
+ {
3208
+ "action": "pick_up",
3209
+ "node": {
3210
+ "name": "complimentary_tshirt",
3211
+ "id": 6
3212
+ }
3213
+ },
3214
+ {
3215
+ "action": "go_to",
3216
+ "node": {
3217
+ "name": "admin",
3218
+ "id": 1
3219
+ }
3220
+ },
3221
+ {
3222
+ "action": "put_on",
3223
+ "node": {
3224
+ "name": "shelf",
3225
+ "id": 1
3226
+ }
3227
+ }
3228
+ ]
3229
+ },
3230
+ {
3231
+ "name": "I am hungry. Bring me an apple from Peter and a pepsi from Tobi. I am at the lunch table.",
3232
+ "important_objects": [
3233
+ {
3234
+ "name": "apple",
3235
+ "id": 3
3236
+ },
3237
+ {
3238
+ "name": "pepsi",
3239
+ "id": 1
3240
+ },
3241
+ {
3242
+ "name": "cabinet",
3243
+ "id": 2
3244
+ },
3245
+ {
3246
+ "name": "desk",
3247
+ "id": 38
3248
+ },
3249
+ {
3250
+ "name": "lunch_table",
3251
+ "id": 1
3252
+ }
3253
+ ],
3254
+ "init_conditions": null,
3255
+ "goal_conditions": [
3256
+ {
3257
+ "node": {
3258
+ "name": "apple",
3259
+ "id": 3
3260
+ },
3261
+ "relation": "ontop_of",
3262
+ "related_to": {
3263
+ "name": "lunch_table",
3264
+ "id": 1
3265
+ },
3266
+ "states": null
3267
+ },
3268
+ {
3269
+ "node": {
3270
+ "name": "pepsi",
3271
+ "id": 1
3272
+ },
3273
+ "relation": "ontop_of",
3274
+ "related_to": {
3275
+ "name": "lunch_table",
3276
+ "id": 1
3277
+ },
3278
+ "states": null
3279
+ }
3280
+ ],
3281
+ "actions": [
3282
+ {
3283
+ "action": "go_to",
3284
+ "node": {
3285
+ "name": "peters_office",
3286
+ "id": 1
3287
+ }
3288
+ },
3289
+ {
3290
+ "action": "open",
3291
+ "node": {
3292
+ "name": "cabinet",
3293
+ "id": 2
3294
+ }
3295
+ },
3296
+ {
3297
+ "action": "pick_up",
3298
+ "node": {
3299
+ "name": "apple",
3300
+ "id": 3
3301
+ }
3302
+ },
3303
+ {
3304
+ "action": "close",
3305
+ "node": {
3306
+ "name": "cabinet",
3307
+ "id": 2
3308
+ }
3309
+ },
3310
+ {
3311
+ "action": "go_to",
3312
+ "node": {
3313
+ "name": "cafeteria",
3314
+ "id": 1
3315
+ }
3316
+ },
3317
+ {
3318
+ "action": "put_on",
3319
+ "node": {
3320
+ "name": "lunch_table",
3321
+ "id": 1
3322
+ }
3323
+ },
3324
+ {
3325
+ "action": "go_to",
3326
+ "node": {
3327
+ "name": "tobis_office",
3328
+ "id": 1
3329
+ }
3330
+ },
3331
+ {
3332
+ "action": "pick_up",
3333
+ "node": {
3334
+ "name": "pepsi",
3335
+ "id": 1
3336
+ }
3337
+ },
3338
+ {
3339
+ "action": "go_to",
3340
+ "node": {
3341
+ "name": "cafeteria",
3342
+ "id": 1
3343
+ }
3344
+ },
3345
+ {
3346
+ "action": "put_on",
3347
+ "node": {
3348
+ "name": "lunch_table",
3349
+ "id": 1
3350
+ }
3351
+ }
3352
+ ]
3353
+ },
3354
+ {
3355
+ "name": "Lets play a prank with chair on Niko. Dimity might have something.",
3356
+ "important_objects": [
3357
+ {
3358
+ "name": "buzzer",
3359
+ "id": 1
3360
+ },
3361
+ {
3362
+ "name": "desk",
3363
+ "id": 3
3364
+ },
3365
+ {
3366
+ "name": "cabinet",
3367
+ "id": 1
3368
+ }
3369
+ ],
3370
+ "init_conditions": null,
3371
+ "goal_conditions": [
3372
+ {
3373
+ "node": {
3374
+ "name": "buzzer",
3375
+ "id": 1
3376
+ },
3377
+ "relation": "ontop_of",
3378
+ "related_to": {
3379
+ "name": "chair",
3380
+ "id": 1
3381
+ },
3382
+ "states": null
3383
+ }
3384
+ ],
3385
+ "actions": [
3386
+ {
3387
+ "action": "go_to",
3388
+ "node": {
3389
+ "name": "dimitys_office",
3390
+ "id": 1
3391
+ }
3392
+ },
3393
+ {
3394
+ "action": "pick_up",
3395
+ "node": {
3396
+ "name": "buzzer",
3397
+ "id": 1
3398
+ }
3399
+ },
3400
+ {
3401
+ "action": "go_to",
3402
+ "node": {
3403
+ "name": "nikos_office",
3404
+ "id": 1
3405
+ }
3406
+ },
3407
+ {
3408
+ "action": "put_on",
3409
+ "node": {
3410
+ "name": "chair",
3411
+ "id": 1
3412
+ }
3413
+ }
3414
+ ]
3415
+ },
3416
+ {
3417
+ "name": "There is an office which has a cabinet containing a rotten apple. The cabinet name contains an odd number. Locate the office, throw away the fruit and get them a fresh apple.",
3418
+ "important_objects": [
3419
+ {
3420
+ "name": "cabinet",
3421
+ "id": 3
3422
+ },
3423
+ {
3424
+ "name": "apple",
3425
+ "id": 2
3426
+ },
3427
+ {
3428
+ "name": "rubbish_bin",
3429
+ "id": 1
3430
+ },
3431
+ {
3432
+ "name": "apple",
3433
+ "id": 1
3434
+ }
3435
+ ],
3436
+ "init_conditions": null,
3437
+ "goal_conditions": [
3438
+ {
3439
+ "node": {
3440
+ "name": "apple",
3441
+ "id": 2
3442
+ },
3443
+ "relation": "inside_of",
3444
+ "related_to": {
3445
+ "name": "rubbish_bin",
3446
+ "id": 1
3447
+ },
3448
+ "states": null
3449
+ },
3450
+ {
3451
+ "node": {
3452
+ "name": "apple",
3453
+ "id": 1
3454
+ },
3455
+ "relation": "inside_of",
3456
+ "related_to": {
3457
+ "name": "cabinet",
3458
+ "id": 3
3459
+ },
3460
+ "states": null
3461
+ }
3462
+ ],
3463
+ "actions": [
3464
+ {
3465
+ "action": "go_to",
3466
+ "node": {
3467
+ "name": "dimitys_office",
3468
+ "id": 1
3469
+ }
3470
+ },
3471
+ {
3472
+ "action": "open",
3473
+ "node": {
3474
+ "name": "cabinet",
3475
+ "id": 3
3476
+ }
3477
+ },
3478
+ {
3479
+ "action": "pick_up",
3480
+ "node": {
3481
+ "name": "apple",
3482
+ "id": 2
3483
+ }
3484
+ },
3485
+ {
3486
+ "action": "go_to",
3487
+ "node": {
3488
+ "name": "kitchen",
3489
+ "id": 1
3490
+ }
3491
+ },
3492
+ {
3493
+ "action": "open",
3494
+ "node": {
3495
+ "name": "rubbish_bin",
3496
+ "id": 1
3497
+ }
3498
+ },
3499
+ {
3500
+ "action": "put_inside",
3501
+ "node": {
3502
+ "name": "rubbish_bin",
3503
+ "id": 1
3504
+ }
3505
+ },
3506
+ {
3507
+ "action": "close",
3508
+ "node": {
3509
+ "name": "rubbish_bin",
3510
+ "id": 1
3511
+ }
3512
+ },
3513
+ {
3514
+ "action": "go_to",
3515
+ "node": {
3516
+ "name": "wills_office",
3517
+ "id": 1
3518
+ }
3519
+ },
3520
+ {
3521
+ "action": "open",
3522
+ "node": {
3523
+ "name": "cabinet",
3524
+ "id": 4
3525
+ }
3526
+ },
3527
+ {
3528
+ "action": "pick_up",
3529
+ "node": {
3530
+ "name": "apple",
3531
+ "id": 1
3532
+ }
3533
+ },
3534
+ {
3535
+ "action": "close",
3536
+ "node": {
3537
+ "name": "cabinet",
3538
+ "id": 4
3539
+ }
3540
+ },
3541
+ {
3542
+ "action": "go_to",
3543
+ "node": {
3544
+ "name": "dimitys_office",
3545
+ "id": 1
3546
+ }
3547
+ },
3548
+ {
3549
+ "action": "put_inside",
3550
+ "node": {
3551
+ "name": "cabinet",
3552
+ "id": 3
3553
+ }
3554
+ },
3555
+ {
3556
+ "action": "close",
3557
+ "node": {
3558
+ "name": "cabinet",
3559
+ "id": 3
3560
+ }
3561
+ }
3562
+ ]
3563
+ }
3564
+ ]
office/office_graph.py ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import networkx as nx
2
+ from nodes import ROOMS, OFFICES, ASSETS, OBJECTS
3
+
4
+ def add_edges(graph):
5
+ for node_name in graph.nodes:
6
+ node = graph.nodes[node_name]
7
+ match node['type']:
8
+ case 'place':
9
+ graph.add_edge(node_name,('scene',1))
10
+ case 'asset':
11
+ graph.add_edge(node_name,node['place'])
12
+ case 'object':
13
+ graph.add_edge(node_name,node['related_to'])
14
+ case 'agent':
15
+ graph.add_edge(node_name,node['location'])
16
+ case 'scene':
17
+ pass
18
+ case _:
19
+ print(f"Unknown node type: {node['type']}")
20
+
21
+ def create_office_graph():
22
+ """Initializes and builds the office scene graph."""
23
+ graph = nx.Graph()
24
+ graph.add_node(('scene', 1), name='SayPlan Office', type='scene')
25
+
26
+ # Add places (offices and rooms) and connect them to the scene
27
+ for place in (OFFICES + ROOMS):
28
+ graph.add_node(place, type='place')
29
+
30
+ # Add assets and connect them to their places
31
+ for asset, place, states, affordances, properties in ASSETS:
32
+ graph.add_node(asset, place=place, states=states, affordances=affordances, properties=properties, type='asset')
33
+
34
+ # Add objects and connect them to their related assets/objects
35
+ for obj, relation, related_to, states, affordances, properties in OBJECTS:
36
+ graph.add_node(obj, relation=relation, related_to=related_to, states=states, affordances=affordances, properties=properties, type='object')
37
+
38
+ # Add the agent and connect it to its location
39
+ agent_node = ('agent', 1)
40
+ agent_location = ('mobile_robotics_lab', 1)
41
+ graph.add_node(agent_node, location=agent_location, holding='', type='agent')
42
+ add_edges(graph)
43
+ return graph
44
+
45
+ # Initialize the graph by calling the function
46
+ office_graph = create_office_graph()
validator.py ADDED
@@ -0,0 +1,287 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import networkx as nx
2
+ import copy
3
+
4
+ MAX_OBJECTS_DEEP = 10
5
+
6
+ def validate_plan(init_graph, goal_graph, actions, print_results=False):
7
+ #Find nodes changed betwee initial and goal graph.
8
+ important_nodes = find_important_nodes(init_graph, goal_graph, add_assets=False)
9
+ if print_results:
10
+ print("Important nodes:\n",important_nodes)
11
+ #Run actions in graph simulation
12
+ final_graph, errors = simulate_on_graph(init_graph, actions)
13
+
14
+ #Classes of important objects
15
+ important_node_names = []
16
+ for node in important_nodes:
17
+ if node[0] not in important_node_names:
18
+ important_node_names.append(node[0])
19
+
20
+ correct_obj, total_obj = validate_objects(final_graph, goal_graph, important_node_names, print_results)
21
+ correct_assets, total_asets = validate_assets(final_graph, goal_graph, important_nodes)
22
+
23
+ object_success_rate = 1.0 if total_obj == 0 else correct_obj / total_obj
24
+ asset_success_rate = 1.0 if total_asets == 0 else correct_assets / total_asets
25
+
26
+ total_count = total_obj + total_asets
27
+ partial_success = 1.0 if total_count == 0 else (correct_obj + correct_assets) / total_count
28
+
29
+ if print_results:
30
+ print("Object Success Rate:", object_success_rate)
31
+ print("Asset Success Rate:", asset_success_rate)
32
+ print("Partial Success:", partial_success)
33
+ print(errors)
34
+
35
+ if len(errors) == 0 and partial_success == 1.0:
36
+ success = True
37
+ else:
38
+ success = False
39
+
40
+ return success, partial_success, errors
41
+
42
+ def simulate_on_graph(init_graph, actions):
43
+ simulator = ValidatorSceneSimulator(init_graph)
44
+ errors = []
45
+ for action in actions:
46
+ feedback = simulator.action(action[0], action[1])
47
+ if feedback:
48
+ errors.append((action, feedback))
49
+ final_graph = simulator.graph
50
+ return final_graph, errors
51
+
52
+ def validate_objects(final_graph, goal_graph, important_node_names, print_results=False):
53
+ object_count = 0
54
+ goal_state_counts = {}
55
+ final_state_counts = {}
56
+ # Find all objects with same name as relevant node names. (Objects of same class)
57
+ for node_name in goal_graph:
58
+ goal_node = goal_graph.nodes[node_name]
59
+ final_node = final_graph.nodes[node_name]
60
+ if node_name[0] in important_node_names and goal_node['type'] == 'object':
61
+ object_count += 1
62
+ goal_state = (node_name[0], tuple(goal_node['states']), goal_node['relation'], goal_node['related_to'])
63
+ final_state = (node_name[0], tuple(final_node['states']), final_node['relation'], final_node['related_to'])
64
+
65
+ goal_state_counts[goal_state] = goal_state_counts.get(goal_state, 0) + 1
66
+ final_state_counts[final_state] = final_state_counts.get(final_state, 0) + 1
67
+ state_difference = 0
68
+ # Count objects in correct states
69
+ for key in goal_state_counts:
70
+ if key in final_state_counts:
71
+ goal_state_counts[key] -= final_state_counts[key]
72
+ if goal_state_counts[key] < 0:
73
+ goal_state_counts[key] = 0
74
+ state_difference += goal_state_counts[key]
75
+ correct_objects = object_count - state_difference
76
+ if print_results:
77
+ print("Goal state count:")
78
+ for goal in goal_state_counts:
79
+ print(goal, goal_state_counts[goal], sep=': ')
80
+ print("Final state count:")
81
+ for goal in final_state_counts:
82
+ print(goal, final_state_counts[goal], sep=': ')
83
+
84
+ return correct_objects, object_count
85
+
86
+ def validate_assets(final_graph, goal_graph, important_nodes):
87
+ # Check Asset states
88
+ asset_count = 0
89
+ correct_states = 0
90
+ for node_name in important_nodes:
91
+ final_node = final_graph.nodes[node_name]
92
+ goal_node = goal_graph.nodes[node_name]
93
+ if final_node['type'] == 'asset':
94
+ asset_count += 1
95
+ if set(final_node['states']) == set(goal_node['states']):
96
+ correct_states += 1
97
+ return correct_states, asset_count
98
+
99
+ class ValidatorSceneSimulator():
100
+ def __init__(self, graph: nx.Graph):
101
+ self.graph = copy.deepcopy(graph)
102
+ self._reset_edges()
103
+
104
+ def _reset_edges(self):
105
+ self.graph.remove_edges_from(list(self.graph.edges))
106
+ for node_name in self.graph.nodes:
107
+ self._add_edge(node_name)
108
+
109
+ def _add_edge(self, node_name):
110
+ node = self.graph.nodes[node_name]
111
+ try:
112
+ match node['type']:
113
+ case 'place':
114
+ self.graph.add_edge(node_name,('scene',1))
115
+ case 'asset':
116
+ self.graph.add_edge(node_name,node['place'])
117
+ case 'object':
118
+ self.graph.add_edge(node_name,node['related_to'])
119
+ case 'unseen_object':
120
+ self.graph.add_edge(node_name,node['related_to'])
121
+ case 'agent':
122
+ self.graph.add_edge(node_name,node['location'])
123
+ case 'scene':
124
+ pass
125
+ case _:
126
+ print(f"Unknown node type: {node['type']}")
127
+ except:
128
+ raise ValueError(f"Error during edges resetting with {node_name} {node}. Check relations.")
129
+
130
+ def is_accessible(self, node):
131
+ if node['type'] != 'object':
132
+ return True, ''
133
+ for _ in range(MAX_OBJECTS_DEEP):
134
+ parent_name = node['related_to']
135
+ parent = self.graph.nodes[parent_name]
136
+ if parent['type'] == 'agent':
137
+ return True, ''
138
+ if 'closed' in parent['states'] and node['relation'] == 'inside_of':
139
+ return False, parent_name
140
+ if parent['type'] != 'object':
141
+ return True, ''
142
+ node = parent
143
+ return True, ''
144
+
145
+ def find_place(self, node):
146
+ for _ in range(MAX_OBJECTS_DEEP+1):
147
+ if node['type'] == 'asset':
148
+ return node['place']
149
+ if node['type'] == 'agent':
150
+ return node['location']
151
+ parent_name = node['related_to']
152
+ node = self.graph.nodes[parent_name]
153
+
154
+ def action(self, action, node_name):
155
+ G = self.graph
156
+ if action in ['done', 'discover_objects']:
157
+ return 0
158
+ if node_name not in G:
159
+ return f"Node {node_name} not found in the graph. Try look on or inside assets."
160
+ if action not in ['put_on', 'put_inside', 'pick_up', 'open', 'close', 'turn_on', 'turn_off', 'discover_objects', 'go_to']:
161
+ return f"Action {action} is wrong. No such action as {action}."
162
+
163
+ node = G.nodes[node_name]
164
+ agent = G.nodes[('agent',1)]
165
+ sayplan_name = node_name[0] +'-'+ str(node_name[1])
166
+
167
+ if action in ['put_on', 'put_inside', 'pick_up', 'open', 'close', 'turn_on', 'turn_off', 'discover_objects'] and node['type'] not in ['asset', 'object']:
168
+ return f"Action {action}({sayplan_name}) is wrong. You can interact only with asset and object nodes."
169
+
170
+ accesible, parent_name = self.is_accessible(node)
171
+ if not accesible:
172
+ return f"Action {action}({sayplan_name}) is wrong.{sayplan_name} in not accesible because {parent_name} is closed."
173
+
174
+ if node['type'] in ['asset', 'object'] and action not in node['affordances']:
175
+ return f"Action {action}({sayplan_name}) is wrong. It is not possible to {action} {sayplan_name}"
176
+
177
+ if action not in ['go_to', 'done'] and agent['location'] != self.find_place(node):
178
+ return f"Action {action}({sayplan_name}) is wrong. Agent not in the same room with node."
179
+
180
+ match action:
181
+ case 'go_to':
182
+ if node['type'] != 'place':
183
+ return f"Action {action}({sayplan_name}) is wrong. {sayplan_name} is not a room to go."
184
+ agent['location'] = node_name
185
+
186
+ case 'pick_up':
187
+ if agent['holding'] != '':
188
+ return f"Action {action}({sayplan_name}) is wrong. Agent can hold only one object. Agent aldeady holding {agent['holding']}"
189
+ if (node['type'] != 'object'):
190
+ return f"Action {action}({sayplan_name}) is wrong. Agent can pick_up only object nodes."
191
+
192
+ agent['holding'] = node_name
193
+ node['relation'] = 'inside_hand'
194
+ node['related_to'] = ('agent',1)
195
+ case 'put_on':
196
+ if agent['holding'] == '':
197
+ return f"Action {action}({sayplan_name}) is wrong. Agent don't holding something to put"
198
+ if 'put_on' not in node['affordances']:
199
+ return f"Action {action}({sayplan_name}) is wrong. Agent cant put objects on {sayplan_name}"
200
+
201
+ G.nodes[agent['holding']]['relation'] = 'ontop_of'
202
+ G.nodes[agent['holding']]['related_to'] = node_name
203
+ agent['holding'] = ''
204
+
205
+ case 'put_inside':
206
+ if agent['holding'] == '':
207
+ return f"Action {action}({sayplan_name}) is wrong. Agent don't holding something to put"
208
+ if agent['holding'] == node:
209
+ return f"Action {action}({sayplan_name}) is wrong. An object cannot be placed inside itself."
210
+ if 'closed' in node['states']:
211
+ return f"Action {action}({sayplan_name}) is wrong. Agent cant put objects inside of closed {sayplan_name}"
212
+
213
+ G.nodes[agent['holding']]['relation'] = 'inside_of'
214
+ G.nodes[agent['holding']]['related_to'] = node_name
215
+ agent['holding'] = ''
216
+ case 'open':
217
+ if 'open' in node['states']:
218
+ return f"Action {action}({sayplan_name}) is wrong. {sayplan_name} already open"
219
+
220
+ node['states'].remove('closed')
221
+ node['states'].append('open')
222
+ case 'close':
223
+ if 'closed' in node['states']:
224
+ return f"Action {action}({sayplan_name}) is wrong. {sayplan_name} already closed"
225
+
226
+ node['states'].remove('open')
227
+ node['states'].append('closed')
228
+ case 'turn_on':
229
+ if 'on' in node['states']:
230
+ return f"Action {action}({sayplan_name}) is wrong. {sayplan_name} already turned on"
231
+
232
+ if 'off' in node['states']:
233
+ node['states'].remove('off')
234
+ node['states'].append('on')
235
+
236
+ #Adding states for dynamic tasks from SayPlan
237
+ if node_name[0] in ['microwave'] and 'closed' in node['states']:
238
+ for obj, attr in G.nodes(data=True):
239
+ if attr['type'] == 'object' and attr['related_to'] == node_name and attr['relation'] == 'inside_of':
240
+ attr['states'].append('hot')
241
+ if node_name[0] in ['coffee_machine']:
242
+ for obj, attr in G.nodes(data=True):
243
+ if attr['type'] == 'object' and attr['related_to'] == node_name and attr['relation'] == 'inside_of':
244
+ attr['states'].append('filled_coffee')
245
+
246
+ case 'turn_off':
247
+ if 'off' in node['states']:
248
+ return f"Action {action}({sayplan_name}) is wrong. {sayplan_name} already off"
249
+
250
+ node['states'].remove('on')
251
+ node['states'].append('off')
252
+
253
+ case 'discover_objects':
254
+ pass
255
+ case 'done':
256
+ pass
257
+ case _:
258
+ return f"Action {action} is wrong. No such action as {action}."
259
+ self._reset_edges()
260
+ return 0
261
+
262
+ def find_important_nodes(init_graph, goal_graph, add_assets=False):
263
+ """
264
+ Function that return list of objects and assets changed between initial and goal graph.
265
+ """
266
+ def add_parent_nodes(node_name, graph):
267
+ node = graph.nodes[node_name]
268
+ for _ in range(MAX_OBJECTS_DEEP):
269
+ parent_name = node.get('related_to')
270
+ if not parent_name:
271
+ break
272
+ parent = graph.nodes[parent_name]
273
+ important_nodes.add(parent_name)
274
+ if parent['type'] != 'object':
275
+ break
276
+ node = parent
277
+
278
+ important_nodes = set()
279
+ for node_name in init_graph.nodes:
280
+ if init_graph.nodes[node_name] != goal_graph.nodes[node_name]:
281
+ important_nodes.add(node_name)
282
+
283
+ if init_graph.nodes[node_name]['type'] == 'object' and add_assets:
284
+ add_parent_nodes(node_name, init_graph)
285
+ add_parent_nodes(node_name, goal_graph)
286
+
287
+ return list(important_nodes)
virtualhome/virtualhome317.json ADDED
The diff for this file is too large to render. See raw diff
 
virtualhome/virtualhome317.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:c611683d7115c609fb8b437cde290955694ae7c03a35c9bc5f4a74f6bfecf7f6
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+ size 7449321