Hydra: Marker-Free RGB-D Hand-Eye Calibration

Abstract:This work presents an RGB-D imaging-based approach to marker-free hand-eye calibration using a novel implementation of the iterative closest point (ICP) algorithm with a robust point-to-plane (PTP) objective formulated on a Lie algebra. Its applicability is demonstrated through comprehensive experiments using three well known serial manipulators and two RGB-D cameras. With only three randomly chosen robot configurations, our approach achieves approximately 90% successful calibrations, demonstrating 2-3x higher convergence rates to the global optimum compared to both marker-based and marker-free baselines. We also report 2 orders of magnitude faster convergence time (0.8 +/- 0.4 s) for 9 robot configurations over other marker-free methods. Our method exhibits significantly improved accuracy (5 mm in task space) over classical approaches (7 mm in task space) whilst being marker-free. The benchmarking dataset and code are open sourced under Apache 2.0 License, and a ROS 2 integration with robot abstraction is provided to facilitate deployment.

Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)

arXiv:2504.20584 [cs.RO]

(or arXiv:2504.20584v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2504.20584 Focus to learn more arXiv-issued DOI via DataCite

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