PANOS: Payload-Aware Navigation in Offroad Scenarios
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913517243727872 |
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| author | Singh, Kartikeya Turkar, Yash Aluckal, Christo Adhivarahan, Charuvarahan Dantu, Karthik |
| author_facet | Singh, Kartikeya Turkar, Yash Aluckal, Christo Adhivarahan, Charuvarahan Dantu, Karthik |
| contents | Nature has evolved humans to walk on different terrains by developing a detailed understanding of their physical characteristics. Similarly, legged robots need to develop their capability to walk on complex terrains with a variety of task-dependent payloads to achieve their goals. However, conventional terrain adaptation methods are susceptible to failure with varying payloads. In this work, we introduce PANOS, a weakly supervised approach that integrates proprioception and exteroception from onboard sensing to achieve a stable gait while walking by a legged robot over various terrains. Our work also provides evidence of its adaptability over varying payloads. We evaluate our method on multiple terrains and payloads using a legged robot. PANOS improves the stability up to 44% without any payload and 53% with 15 lbs payload. We also notice a reduction in the vibration cost of 20% with the payload for various terrain types when compared to state-of-the-art methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_16566 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PANOS: Payload-Aware Navigation in Offroad Scenarios Singh, Kartikeya Turkar, Yash Aluckal, Christo Adhivarahan, Charuvarahan Dantu, Karthik Robotics Nature has evolved humans to walk on different terrains by developing a detailed understanding of their physical characteristics. Similarly, legged robots need to develop their capability to walk on complex terrains with a variety of task-dependent payloads to achieve their goals. However, conventional terrain adaptation methods are susceptible to failure with varying payloads. In this work, we introduce PANOS, a weakly supervised approach that integrates proprioception and exteroception from onboard sensing to achieve a stable gait while walking by a legged robot over various terrains. Our work also provides evidence of its adaptability over varying payloads. We evaluate our method on multiple terrains and payloads using a legged robot. PANOS improves the stability up to 44% without any payload and 53% with 15 lbs payload. We also notice a reduction in the vibration cost of 20% with the payload for various terrain types when compared to state-of-the-art methods. |
| title | PANOS: Payload-Aware Navigation in Offroad Scenarios |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.16566 |