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arXiv · 2110.01749

Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing

Xiao Li·Yutong Li·Nan Li·Anouck Girard·Ilya Kolmanovsky
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Abstract

In this paper, we introduce a set-theoretic approach for mobile robot localization with infrastructure-based sensing. The proposed method computes sets that over-bound the robot body and orientation under an assumption of known noise bounds on the sensor and robot motion model. We establish theoretical properties and computational approaches for this set-theoretic localization approach and illustrate its application to an automated valet parking example in simulations and to omnidirectional robot localization problems in real-world experiments. We demonstrate that the set-theoretic localization method can perform robustly against uncertainty set initialization and sensor noises compared to the FastSLAM.

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Xiao Li, Yutong Li, Nan Li, Anouck Girard, Ilya Kolmanovsky. 2021-10-04. Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing. https://doi.org/10.1002/adc2.117

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