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JRM Vol.35 No.2 pp. 262-270
doi: 10.20965/jrm.2023.p0262
(2023)

Paper:

MGV Obstacle Avoidance Trajectory Generation Considering Vehicle Shape

Yoshihide Arai, Takashi Sago, Yuki Ueyama, and Masanori Harada

National Defense Academy of Japan
1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan

Received:
September 30, 2022
Accepted:
December 26, 2022
Published:
April 20, 2023
Keywords:
trajectory generation, convex optimization, autonomous vehicle, optimal control
Abstract

This study investigates the application of obstacle avoidance trajectory generation considering the vehicle shape of a micro ground vehicle by successive convexification and state-triggered constraints. The avoidance trajectory is generated by numerical computation and path-following experiments are conducted to assess the generated trajectory. The numerical computation results indicate that the trajectory obtained by the algorithm successfully avoids obstacles considering the vehicle shape and satisfies the constraints. The experiment includes the model predictive control to follow the generated trajectory. Numerical computations and experiments confirm the usefulness of the trajectory generation algorithm.

Obstacle avoidance by compound STCs

Obstacle avoidance by compound STCs

Cite this article as:
Y. Arai, T. Sago, Y. Ueyama, and M. Harada, “MGV Obstacle Avoidance Trajectory Generation Considering Vehicle Shape,” J. Robot. Mechatron., Vol.35 No.2, pp. 262-270, 2023.
Data files:
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Last updated on Apr. 05, 2024