Add robotics task category and improve documentation

Hi there, I'm Niels from the Hugging Face community science team. This PR adds the `robotics` task category to the metadata and improves the dataset card with links to the official paper, code repository, and project page. I've also added a sample usage section based on the training scripts provided in the official repository.

README.md

@@ -1,5 +1,7 @@
 ---
 license: mit
+task_categories:
+- robotics
 configs:
 - config_name: default
   data_files:
@@ -34,6 +36,23 @@ dataset_info:
 
 # SafeFlowMPC Finetuning Dataset
 
-SafeFlowMPC finetuning dataset that is used in this paper: [SafeFlowMPC Paper](https://arxiv.org/abs/2602.12794). 
+This repository contains the finetuning dataset used in the paper [SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies](https://huggingface.co/papers/2602.12794). 
 
-The code for training and inference is available at [SafeFlowMPC Github](https://github.com/TU-Wien-ACIN-CDS/SafeFlowMPC).
+SafeFlowMPC is a method that combines flow matching and online optimization to achieve safe and flexible robotic manipulation. This specific dataset is used for the finetuning stage to incorporate safety considerations into the model.
+
+- **Paper:** [SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies](https://huggingface.co/papers/2602.12794)
+- **Code:** [SafeFlowMPC GitHub](https://github.com/TU-Wien-ACIN-CDS/SafeFlowMPC)
+- **Project Page:** [https://www.acin.tuwien.ac.at/en/42d6](https://www.acin.tuwien.ac.at/en/42d6)
+
+## Usage
+
+This dataset is designed to be used with the SafeFlowMPC training scripts. To finetune a model on this dataset with safety considerations, you can use the following command from the official repository:
+
+```bash
+python train_imitation_learning_safe.py
+```
+
+The script is configured to load this dataset automatically from the Hugging Face Hub.
+
+## Dataset Creation
+The dataset was created using the VP-STO planner. It contains safe intermediate trajectories generated to train the flow matching model for precise and safe robotic tasks, such as grasping and human-robot object handovers on a KUKA 7-DoF manipulator.