Create an open-source bridge that maps differentiable simulation results directly to reinforcement learning control policies. This would enable faster iterations for hardware-in-the-loop robotics training.
Suggested repo: warp-gym
"High-fidelity GPU physics for your RL agents, now fully differentiable."
Estimated effort: 120h