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arXiv 2203.00602cs.RO

Humanoid Path Planning over Rough Terrain using Traversability Assessment

Institute of Human and Machine Cognition(人类与机器认知研究所);University of West Florida(西佛罗里达大学);Pusan National University(釜山国立大学);Boardwalk Robotics, Inc.(Boardwalk机器人公司)

Stephen McCrory, Bhavyansh Mishra, Jaehoon An, Robert Griffin, Jerry Pratt, Hakki Erhan Sevil

英文摘要:

We present a planning framework designed for humanoid navigation over challenging terrain. This framework is designed to plan a traversable, smooth, and collision-free path using a 2.5D height map. The planner is comprised of two stages. The first stage consists of an A* planner which reasons about traversability using terrain features. A novel cost function is presented which encodes the bipedal gait directly into the graph structure, enabling natural paths that are robust to small gaps in traversability. The second stage is an optimization framework which smooths the path while further improving traversability. The planner is tested on a variety of terrains in simulation and is combined with a footstep planner and balance controller to create an integrated navigation framework, which is demonstrated on a DRC Boston Dynamics Atlas robot.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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