MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866916342429384704 |
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| author | Meser, Moritz Bhatt, Aditya Belousov, Boris Peters, Jan |
| author_facet | Meser, Moritz Bhatt, Aditya Belousov, Boris Peters, Jan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00342 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench Meser, Moritz Bhatt, Aditya Belousov, Boris Peters, Jan Robotics Artificial Intelligence Machine Learning 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. |
| title | MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench |
| topic | Robotics Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2408.00342 |