ConstructTraining / scripts /tutorials /01_assets /run_deformable_object.py
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# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause
"""
This script demonstrates how to work with the deformable object and interact with it.
.. code-block:: bash
# Usage
./isaaclab.sh -p scripts/tutorials/01_assets/run_deformable_object.py
"""
"""Launch Isaac Sim Simulator first."""
import argparse
from isaaclab.app import AppLauncher
# add argparse arguments
parser = argparse.ArgumentParser(description="Tutorial on interacting with a deformable object.")
# append AppLauncher cli args
AppLauncher.add_app_launcher_args(parser)
# parse the arguments
args_cli = parser.parse_args()
# launch omniverse app
app_launcher = AppLauncher(args_cli)
simulation_app = app_launcher.app
"""Rest everything follows."""
import torch
import isaaclab.sim as sim_utils
import isaaclab.utils.math as math_utils
from isaaclab.assets import DeformableObject, DeformableObjectCfg
from isaaclab.sim import SimulationContext
def design_scene():
"""Designs the scene."""
# Ground-plane
cfg = sim_utils.GroundPlaneCfg()
cfg.func("/World/defaultGroundPlane", cfg)
# Lights
cfg = sim_utils.DomeLightCfg(intensity=2000.0, color=(0.8, 0.8, 0.8))
cfg.func("/World/Light", cfg)
# Create separate groups called "Origin1", "Origin2", "Origin3"
# Each group will have a robot in it
origins = [[0.25, 0.25, 0.0], [-0.25, 0.25, 0.0], [0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]]
for i, origin in enumerate(origins):
sim_utils.create_prim(f"/World/Origin{i}", "Xform", translation=origin)
# Deformable Object
cfg = DeformableObjectCfg(
prim_path="/World/Origin.*/Cube",
spawn=sim_utils.MeshCuboidCfg(
size=(0.2, 0.2, 0.2),
deformable_props=sim_utils.DeformableBodyPropertiesCfg(rest_offset=0.0, contact_offset=0.001),
visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.5, 0.1, 0.0)),
physics_material=sim_utils.DeformableBodyMaterialCfg(poissons_ratio=0.4, youngs_modulus=1e5),
),
init_state=DeformableObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 1.0)),
debug_vis=True,
)
cube_object = DeformableObject(cfg=cfg)
# return the scene information
scene_entities = {"cube_object": cube_object}
return scene_entities, origins
def run_simulator(sim: sim_utils.SimulationContext, entities: dict[str, DeformableObject], origins: torch.Tensor):
"""Runs the simulation loop."""
# Extract scene entities
# note: we only do this here for readability. In general, it is better to access the entities directly from
# the dictionary. This dictionary is replaced by the InteractiveScene class in the next tutorial.
cube_object = entities["cube_object"]
# Define simulation stepping
sim_dt = sim.get_physics_dt()
sim_time = 0.0
count = 0
# Nodal kinematic targets of the deformable bodies
nodal_kinematic_target = cube_object.data.nodal_kinematic_target.clone()
# Simulate physics
while simulation_app.is_running():
# reset
if count % 250 == 0:
# reset counters
sim_time = 0.0
count = 0
# reset the nodal state of the object
nodal_state = cube_object.data.default_nodal_state_w.clone()
# apply random pose to the object
pos_w = torch.rand(cube_object.num_instances, 3, device=sim.device) * 0.1 + origins
quat_w = math_utils.random_orientation(cube_object.num_instances, device=sim.device)
nodal_state[..., :3] = cube_object.transform_nodal_pos(nodal_state[..., :3], pos_w, quat_w)
# write nodal state to simulation
cube_object.write_nodal_state_to_sim(nodal_state)
# Write the nodal state to the kinematic target and free all vertices
nodal_kinematic_target[..., :3] = nodal_state[..., :3]
nodal_kinematic_target[..., 3] = 1.0
cube_object.write_nodal_kinematic_target_to_sim(nodal_kinematic_target)
# reset buffers
cube_object.reset()
print("----------------------------------------")
print("[INFO]: Resetting object state...")
# update the kinematic target for cubes at index 0 and 3
# we slightly move the cube in the z-direction by picking the vertex at index 0
nodal_kinematic_target[[0, 3], 0, 2] += 0.001
# set vertex at index 0 to be kinematically constrained
# 0: constrained, 1: free
nodal_kinematic_target[[0, 3], 0, 3] = 0.0
# write kinematic target to simulation
cube_object.write_nodal_kinematic_target_to_sim(nodal_kinematic_target)
# write internal data to simulation
cube_object.write_data_to_sim()
# perform step
sim.step()
# update sim-time
sim_time += sim_dt
count += 1
# update buffers
cube_object.update(sim_dt)
# print the root position
if count % 50 == 0:
print(f"Root position (in world): {cube_object.data.root_pos_w[:, :3]}")
def main():
"""Main function."""
# Load kit helper
sim_cfg = sim_utils.SimulationCfg(device=args_cli.device)
sim = SimulationContext(sim_cfg)
# Set main camera
sim.set_camera_view(eye=[3.0, 0.0, 1.0], target=[0.0, 0.0, 0.5])
# Design scene
scene_entities, scene_origins = design_scene()
scene_origins = torch.tensor(scene_origins, device=sim.device)
# Play the simulator
sim.reset()
# Now we are ready!
print("[INFO]: Setup complete...")
# Run the simulator
run_simulator(sim, scene_entities, scene_origins)
if __name__ == "__main__":
# run the main function
main()
# close sim app
simulation_app.close()