SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning
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Updated
Nov 11, 2025 - Python
SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning
硕士研究生毕业设计总仓
Whole-body motion planning for Unitree G1 humanoid in MuJoCo - ZMP preview control, A* footstep planning, MPC balance (49% energy reduction), RL locomotion, and Jacobian IK manipulation
Python Implementation of Trajectory Generator for ground vehicles
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