PANOS: Payload-Aware Navigation in Offroad Scenarios
<|reference_start|>PANOS: Payload-Aware Navigation in Offroad Scenarios: 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.<|reference_end|>
@article{singh2024panos:,
    title={PANOS: Payload-Aware Navigation in Offroad Scenarios},
    author={Kartikeya Singh, Yash Turkar, Christo Aluckal, Charuvarahan
  Adhivarahan, Karthik Dantu},
    journal={arXiv preprint arXiv:2409.16566},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.16566},
    primaryClass={cs.RO}
}