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Active sensing control improving SLAM accuracy for a vehicle robot

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Abstract

This study considers an autonomous mobile vehicle using SLAM technology in an unknown environment. The focused problem is the decrease of trajectory following accuracy due to the decline of SLAM accuracy in an environment with insufficient information. To solve this problem, we propose to improve overall accuracy by controlling the vehicle’s motion based on the SLAM accuracy. The motion control is implemented as a model predictive control that optimizes an evaluation function including the estimation accuracy. The estimation accuracy is evaluated as the Fisher information concerning the state, especially the velocity. The effectiveness of this method is verified by numerical simulation as compared with a trajectory tracking controller in the same environment.

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Acknowledgements

This work is supported by JSPS Grant-in-Aid for Scientific Research JP19H02098. We would like to express our gratitude.

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Author notes

  1. Kazuma Sekiguchi

    Present address: Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan

Authors and Affiliations

  1. Tokyo City University, 1-28-1, Tamazutsumi, Setagaya, Tokyo, 158-8557, Japan

    Sota Wada & Kenichiro Nonaka

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  1. Kazuma Sekiguchi
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  2. Sota Wada
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  3. Kenichiro Nonaka
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Correspondence to Kazuma Sekiguchi.

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This work was presented in part at the joint symposium of the 27th International Symposium on Artificial Life and Robotics, the 7th International Symposium on BioComplexity, and the 5th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Online, January 25–27, 2022).

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Sekiguchi, K., Wada, S. & Nonaka, K. Active sensing control improving SLAM accuracy for a vehicle robot. Artif Life Robotics 28, 208–216 (2023). https://doi.org/10.1007/s10015-022-00822-2

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  • DOI: https://doi.org/10.1007/s10015-022-00822-2

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