JRM Vol.33 No.6 pp. 1284-1293
doi: 10.20965/jrm.2021.p1284


Autonomous Path Travel Control of Mobile Robot Using Internal and External Camera Images in GPS-Denied Environments

Keita Yamada, Shoya Koga, Takashi Shimoda, and Kazuya Sato

Department of Mechanical Engineering, Faculty of Science and Engineering, Saga University
1 Honjo, Saga, Saga 840-8502, Japan

May 27, 2021
October 26, 2021
December 20, 2021
autonomous motion control of mobile robot, monocular camera, deep learning, GPS-denied environments
Autonomous Path Travel Control of Mobile Robot Using Internal and External Camera Images in GPS-Denied Environments

Autonomous path travel of mobile robot

In this study, we developed a system for calculating the relative position and angle between a mobile robot and a marker using information such as the size of the marker of the internal camera of the mobile robot. Using this information, the mobile robot runs autonomously along the path given by the placement of the marker. In addition, we provide a control system that can follow a trajectory using information obtained by recognizing the mobile robot when reflected in an external camera using deep learning. The proposed method can easily achieve autonomous path travel control for mobile robots in environments where GPS cannot be received. The effectiveness of the proposed system is demonstrated under several actual experiments.

Cite this article as:
Keita Yamada, Shoya Koga, Takashi Shimoda, and Kazuya Sato, “Autonomous Path Travel Control of Mobile Robot Using Internal and External Camera Images in GPS-Denied Environments,” J. Robot. Mechatron., Vol.33, No.6, pp. 1284-1293, 2021.
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Last updated on Jan. 20, 2022