Staircase Recognition and Location Based on Polarization Vision

-- Staircase perception is critical for humanoid robots and mobility -impaired individuals, yet existing methods have low accuracy, lighting sensitivity, and texture dependency. To address this, we propose a novel polarization-visual fusion framework that achieves robust staircase detection and high -precision the three-dimensional (3D) reconstruction, establishing a paradigm of S taircase recognition -- Heterogeneous sensor calibration (monocular and TOF camera) -- Polarization 3D reconstruction . First, the staircase recognition algorithm based on YOLOv11 integrated with polarization-intensity contrast enhancement algorithm and point cloud segmentation is improved, reaching recognition accuracy of 98.7% 0.10% by suppressing reflections and correcting by r edundant information of point cloud. Then, an improved gray wolf optimizer with Levy flight and d ynamic weights enable s accurate heterogeneous sensor calibration ( 0.33 0.04 mm error) between heterogeneous-resolution cameras is employed . Finally, a method of fusing polarized binocular and TOF depth information to realize the 3D reconstruction of the staircase is proposed . Considering the ambiguity in polarization reconstruction and the data holes in binocular reconstruction, b inocular vision is used to correct polarization azimuth ambiguity, TOF is used to fill data holes from stereo matching. Experiments show our method achieves <0.2% reconstruction error at 0.5m - significantly outperforming binocular (surface distortion) and polarization-based (normal vector ambiguity) approaches. This technology provides accurate terrain adaptation for robot ic foothold planning. INTRODUCTION A s a general scene, the staircase interferes with the traversal of h umanoid robots, legged robots, lower limb disabilities, or visually impaired individuals due to its special physical structure. Accurate staircase recognition technology is a prerequisite for navigation and control, and staircase recognition technology has attracted the attention of man y scholars [1],[2],[3] . Staircase recognition is of great significance for the mode switching and foothold position calculation of robots, which can improve the overall performance of robots in stair case scenes. As a common terrain, stairs are very difficult for humanoid robots and people with lower limb disabilities or visual impairments. Therefore, it is of great significance to design a staircase scene perception algorithm. At present, the staircase recognition is mainly applied in the fields of rehabilitation medicine and humanoid robots [ 4 ].