SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies
Paper
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2602.12794
•
Published
Search is not available for this dataset
trajectories
listlengths 112
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| c_data
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| samples
listlengths 10
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| dsamples
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SafeFlowMPC Finetuning Dataset
This repository contains the finetuning dataset used in the paper SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies.
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
- Code: SafeFlowMPC GitHub
- Project Page: 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:
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.
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