人間をマーカーとして用いるロボット間相対姿勢推定
Robot-to-Robot Relative Pose Estimation using Humans as Markers
リーダーロボットがOpenPoseで人間のキーポイントを三角測量し、フォロワーロボットが対応点を介してPnP問題を解くことで、ロボット間の3D相対姿勢を推定する手法を提案した。
著者: Md Jahidul Islam, Jiawei Mo, Junaed Sattar
分類: cs.RO
原文アブストラクト
In this paper, we propose a method to determine the 3D relative pose of pairs of communicating robots by using human pose-based key-points as correspondences. We adopt a 'leader-follower' framework, where at first, the leader robot visually detects and triangulates the key-points using the state-of-the-art pose detector named OpenPose. Afterward, the follower robots match the corresponding 2D projections on their respective calibrated cameras and find their relative poses by solving the perspective-n-point (PnP) problem. In the proposed method, we design an efficient person re-identification technique for associating the mutually visible humans in the scene. Additionally, we present an iterative optimization algorithm to refine the associated key-points based on their local structural properties in the image space. We demonstrate that these refinement processes are essential to establish accurate key-point correspondences across viewpoints. Furthermore, we evaluate the performance of the proposed relative pose estimation system through several experiments conducted in terrestrial and underwater environments. Finally, we discuss the relevant operational challenges of this approach and analyze its feasibility for multi-robot cooperative systems in human-dominated social settings and feature-deprived environments such as underwater.
