Automatic Generation of Multidestination Routes for Autonomous Wheelchairs
Author(s) -
Yusuke Mori,
Katashi Nagao
Publication year - 2020
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2020.p1121
Subject(s) - computer science , wheelchair , image (mathematics) , real time computing , artificial intelligence , simulation , computer vision , world wide web
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom