PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing

Abstract:Recently, biped robot walking technology has been significantly developed, mainly in the context of a bland walking scheme. To emulate human walking, robots need to step on the positions they see in unknown spaces accurately. In this paper, we present PolyMap, a perception-based locomotion planning framework for humanoid robots to climb stairs. Our core idea is to build a real-time polygonal staircase plane semantic map, followed by a footstep planar using these polygonal plane segments. These plane segmentation and visual odometry are done by multi-sensor fusion(LiDAR, RGB-D camera and IMUs). The proposed framework is deployed on a NVIDIA Orin, which performs 20-30 Hz whole-body motion planning output. Both indoor and outdoor real-scene experiments indicate that our method is efficient and robust for humanoid robot stair climbing.

Robotics (cs.RO)

arXiv:2510.12346 [cs.RO]

(or arXiv:2510.12346v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2510.12346 Focus to learn more arXiv-issued DOI via DataCite

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