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Camera-to-Quadruped Robot Pose Estimation from Sequential Images

2026-10-27 03:59:43
Seobin Hwang, Ji-Seong Beom, Yeong-Jun Cho
arXiv_CV
         
Abstract

Quadruped robots are increasingly deployed in hazardous environments such as disaster response and facility inspection, where external-camera monitoring is essential for safe operation. This setting is challenging because quadrupeds are articulated systems with time-varying leg joints, leg symmetry, and frequent self-occlusions, which make keypoint correspondence ambiguous. Moreover, no public benchmark exists, making quantitative comparison difficult. To address these challenges, we propose QuadPose, which estimates the full-body 18-DoF pose (6-DoF base pose + 12-DoF joint angles) from monocular video sequences, and introduce QuadSyn, the first camera-to-quadruped robot pose benchmark. On QuadSyn, QuadPose achieves 92.18% PCK@2.5px, 95.54% PCK-AUC, 85.94% ADD@20cm, 66.98% ADD-AUC, and 3.65 degree mean joint-angle error at approximately 33 FPS.

Abstract (translated)

URL

https://arxiv.org/abs/2610.36599

PDF

https://arxiv.org/pdf/2610.36599.pdf

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