JRM Vol.32 No.6 pp. 1121-1136
doi: 10.20965/jrm.2020.p1121


Automatic Generation of Multidestination Routes for Autonomous Wheelchairs

Yusuke Mori and Katashi Nagao

Graduate School of Informatics, Nagoya University
Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8603, Japan

May 25, 2020
September 30, 2020
December 20, 2020
autonomous wheelchair, multidestination routing, route cost calculation, texture analysis, machine learning

To solve the problem of autonomously navigating multiple destinations, which is one of the tasks in the Tsukuba Challenge 2019, this paper proposes a method for automatically generating the optimal travel route based on costs associated with routes. In the proposed method, the route information is generated by playing back the acquired driving data to perform self-localization, and the self-localization log is stored. In addition, the image group of road surfaces is acquired from the driving data. The costs of routes are generated based on texture analysis of the road surface image group and analysis of the self-localization log. The cost-added route information is generated by combining the costs calculated by the two methods, and by assigning the combined costs to the route. The minimum-cost multidestination route is generated by conducting a route search using cost-added route information. Then, we evaluated the proposed method by comparing it with the method of generating the route using only the distance cost. The results confirmed that the proposed method generates travel routes that account for safety when the autonomous wheelchair is being driven.

Autonomous wheelchair in this research

Autonomous wheelchair in this research

Cite this article as:
Y. Mori and K. Nagao, “Automatic Generation of Multidestination Routes for Autonomous Wheelchairs,” J. Robot. Mechatron., Vol.32 No.6, pp. 1121-1136, 2020.
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