Hand-Eye and Robot-World Calibration by Global Polynomial Optimization

Jan Heller (1) , Didier Henrion (2) , Tomas Pajdla (3)

1 Center for Machine Perception
2 LAAS-MAC - Équipe Méthodes et Algorithmes en Commande
3 Department of Cybernetics [Prague]

The need to relate measurements made by a camera to a different known coordinate system arises in many engineering applications. Historically, it appeared for the first time in the connection with cameras mounted on robotic systems. This problem is commonly known as hand-eye calibration. In this paper, we present several formulations of hand-eye calibration that lead to multivariate polynomial optimization problems. We show that the method of convex linear matrix inequality (LMI) relaxations can be used to effectively solve these problems and to obtain globally optimal solutions. Further, we show that the same approach can be used for the simultaneous hand-eye and robot-world calibration. Finally, we validate the proposed solutions using both synthetic and real datasets.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Optimisation et contrôle [math.OC]

Jan Heller, Didier Henrion, Tomas Pajdla. Hand-Eye and Robot-World Calibration by Global Polynomial Optimization. IEEE International Conference on Robotics and Automation (ICRA 2014), May 2014, Hong Kong, China. 18p. ⟨hal-00946579⟩