Learning Thermal-Aware Locomotion Policies for an Electrically-Actuated Quadruped Robot
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866908860189507584 |
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| author | Qian, Letian Wan, Yuhang Wang, Shuhan Luo, Xin |
| author_facet | Qian, Letian Wan, Yuhang Wang, Shuhan Luo, Xin |
| contents | Electrically-actuated quadrupedal robots possess high mobility on complex terrains, but their motors tend to accumulate heat under high-torque cyclic loads, potentially triggering overheat protection and limiting long-duration tasks. This work proposes a thermal-aware control method that incorporates motor temperatures into reinforcement learning locomotion policies and introduces thermal-constraint rewards to prevent temperature exceedance. Real-world experiments on the Unitree A1 demonstrate that, under a fixed 3 kg payload, the baseline policy triggers overheat protection and stops within approximately 7 minutes, whereas the proposed method can operate continuously for over 27 minutes without thermal interruptions while maintaining comparable command-tracking performance, thereby enhancing sustainable operational capability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_01631 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Learning Thermal-Aware Locomotion Policies for an Electrically-Actuated Quadruped Robot Qian, Letian Wan, Yuhang Wang, Shuhan Luo, Xin Robotics Electrically-actuated quadrupedal robots possess high mobility on complex terrains, but their motors tend to accumulate heat under high-torque cyclic loads, potentially triggering overheat protection and limiting long-duration tasks. This work proposes a thermal-aware control method that incorporates motor temperatures into reinforcement learning locomotion policies and introduces thermal-constraint rewards to prevent temperature exceedance. Real-world experiments on the Unitree A1 demonstrate that, under a fixed 3 kg payload, the baseline policy triggers overheat protection and stops within approximately 7 minutes, whereas the proposed method can operate continuously for over 27 minutes without thermal interruptions while maintaining comparable command-tracking performance, thereby enhancing sustainable operational capability. |
| title | Learning Thermal-Aware Locomotion Policies for an Electrically-Actuated Quadruped Robot |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.01631 |