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MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench

Authors :
Meser, Moritz
Bhatt, Aditya
Belousov, Boris
Peters, Jan
Publication Year :
2024

Abstract

We tackle the recently introduced benchmark for whole-body humanoid control HumanoidBench using MuJoCo MPC. We find that sparse reward functions of HumanoidBench yield undesirable and unrealistic behaviors when optimized; therefore, we propose a set of regularization terms that stabilize the robot behavior across tasks. Current evaluations on a subset of tasks demonstrate that our proposed reward function allows achieving the highest HumanoidBench scores while maintaining realistic posture and smooth control signals. Our code is publicly available and will become a part of MuJoCo MPC, enabling rapid prototyping of robot behaviors.<br />Comment: 3 pages, 3 figures, submitted to IEEE Conference on Robotics and Automation (ICRA@40)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2408.00342
Document Type :
Working Paper