JRM Vol.34 No.5 pp. 1192-1204
doi: 10.20965/jrm.2022.p1192


Waypoint-Based Human-Tracking Navigation for Museum Guide Robot

Kaito Ichihara*, Tadahiro Hasegawa*, Shin’ichi Yuta*, Hirohisa Ichikawa**, and Yoshihide Naruse**

*Shibaura Institute of Technology
3-7-5 Toyosu, Koto-ku, Tokyo 135-8548, Japan

**SANGO Co., Ltd.
3-1 Konosucho, Toyota-shi, Aichi 471-0836, Japan

February 4, 2022
August 5, 2022
October 20, 2022
guidance robot, human-following driving, waypoint navigation, 2D LiDAR, museum
Waypoint-Based Human-Tracking Navigation for Museum Guide Robot

museum guide robot ”EM-Ro”

A visitor-following method that guides visitors as they move around was successfully developed without changing the structure of the waypoint navigation system. We previously developed a guidance robot, “EM-Ro,” to provide guidance services at the ECO35 Muffler Museum, and used the waypoint navigation system to implement a visitor-escort method along a predetermined route. With this visitor-following method, EM-Ro was able to follow a target visitor along visitor-derived waypoints, which were estimated using 2D LiDAR. Thus, the proposed navigation system for the guidance robot provides both visitor-escort and visitor-following guidance services. Using the same waypoint navigation system, it was possible to seamlessly switch between visitor-escort and visitor-following guidance. Switching between prepared or visitor-derived waypoints can make a visitor choose the preferred guidance method. Visitors can switch the guidance method anytime by providing EM-Ro requests from the remote controller. In addition, a guest redetecting method was developed when EM-Ro lost guests. The experimental results at the Muffler Museum showed that both visitor-escort and visitor-following driving by the EM-Ro were successfully demonstrated while guiding guests in the facility.

Cite this article as:
K. Ichihara, T. Hasegawa, S. Yuta, H. Ichikawa, and Y. Naruse, “Waypoint-Based Human-Tracking Navigation for Museum Guide Robot,” J. Robot. Mechatron., Vol.34, No.5, pp. 1192-1204, 2022.
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Last updated on Dec. 01, 2022