JRM Vol.35 No.6 pp. 1489-1502
doi: 10.20965/jrm.2023.p1489


Implementation of Brute-Force Value Iteration for Mobile Robot Path Planning and Obstacle Bypassing

Ryuichi Ueda ORCID Icon, Leon Tonouchi, Tatsuhiro Ikebe, and Yasuo Hayashibara ORCID Icon

Department of Advanced Robotics, Faculty of Advanced Engineering, Chiba Institute of Technology
2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan

May 21, 2023
September 20, 2023
December 20, 2023
mobile robot navigation, obstacle avoidance, dynamic programming, value iteration

We applied a brute-force value iteration algorithm to mobile robot navigation. Value iteration is computationally more expensive than search methods used for navigation. However, it can perfectly calculate the expected cost-to-go from any point in a state space. From this cost data, a robot can know not only the optimal behavior at any position and orientation but also the appropriate detour path against suddenly appearing obstacles. This study implemented value iteration and investigated its properties through experiments with simulated and actual robots. Although its computational cost remained high, our implementation could operate a robot in an actual outdoor environment with 3,700 m2 free space. We also verified that our implementation calculates long detour paths toward closures composed of obstacles.

Avoidance of safety cones and persons

Avoidance of safety cones and persons

Cite this article as:
R. Ueda, L. Tonouchi, T. Ikebe, and Y. Hayashibara, “Implementation of Brute-Force Value Iteration for Mobile Robot Path Planning and Obstacle Bypassing,” J. Robot. Mechatron., Vol.35 No.6, pp. 1489-1502, 2023.
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