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arXiv · 2510.12346

PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing

Bingquan Li·Ning Wang·Zhicheng He·Yucong Wu·Tianwei Zhang
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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.

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Bingquan Li, Ning Wang, Zhicheng He, Yucong Wu, Tianwei Zhang. 2025-10-14. PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing. https://arxiv.org/abs/2510.12346

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