一般化ロボット-世界・ハンドアイキャリブレーションのための証明可能に正しいアルゴリズム
A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
複数のセンサとターゲットの姿勢を同時推定でき、単眼カメラも扱える一般化RWHEC問題に対し、大域的最適性を保証する高速アルゴリズムを提案し、識別可能性条件と誤差有界時の最適性保証を与えた。
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著者: Emmett Wise, Pushyami Kaveti, Qilong Chen, Wenhao Wang, Hanumant Singh, Jonathan Kelly, David M. Rosen, Matthew Giamou
分類: cs.RO
原文アブストラクト
Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computationally efficient, require few assumptions about the structure of the sensing environment, and demand little effort from human operators. In this work, we introduce a fast and certifiably globally optimal algorithm for solving a generalized formulation of the robot-world and hand-eye calibration (RWHEC) problem. The formulation of RWHEC presented is "generalized" in that it supports the simultaneous estimation of multiple sensor and target poses, and permits the use of monocular cameras that, alone, are unable to measure the scale of their environments. In addition to demonstrating our method's superior performance over existing solutions through extensive simulated and real experiments, we derive novel identifiability criteria and establish a priori guarantees of global optimality for problem instances with bounded measurement errors. As part of our analysis, we propose a new constraint qualification for nonlinear programs with redundant constraints; this constraint qualification is of independent interest for establishing the exactness of SDP relaxations of QCQPs that have been tightened through the addition of redundant constraints. Finally, we provide a free and open-source implementation of our algorithms and experiments.
