We propose a certifiably globally optimal approach for solving the hand-eye robot-world problem supporting multiple sensors and targets at once. Further, we leverage this formulation for estimating a geo-referenced calibration of infrastructure sensors. Since vehicle motion recorded by infrastructure sensors is mostly planar, obtaining a unique solution for the respective hand-eye robot-world problem is unfeasible without incorporating additional knowledge. Hence, we extend our proposed method to include a-priori knowledge, i.e., the translation norm of calibration targets, to yield a unique solution. Our approach achieves state-of-the-art results on simulated and real-world data. Especially on real-world intersection data, our approach utilizing the translation norm is the only method providing accurate results.


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    Title :

    Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation


    Contributors:


    Publication date :

    2023-06-04


    Size :

    6392860 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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