metadata
license: mit
task_categories:
- robotics
Combining Constrained Sampling and Reinforcement Learning for Manipulation
This repository contains data associated with the paper Combining Constrained Sampling and Reinforcement Learning for Manipulation.
- Project page: https://www.user.tu-berlin.de/mtoussai/26-CSRL/
- Code: https://github.com/LIS-TU-Berlin/csrl
The paper studies goal-conditioned reinforcement learning for contact-rich manipulation, combining constrained sampling with projected interpolation and curriculum learning to improve exploration and policy learning.