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Navigation Control of an Autonomous Ackerman Robot in Unknown Environments by Using a Lidar-Sensing-Based Fuzzy Controller

Cheng-Jian Lin¹, Jyun-Yu Jhang² and Chen-Chia Chuang¹

1. Department of Computer Science and Information Engineering, National Chin-Yi University of Technology
   Taichung 411, Taiwan
   cjlin@ncut.edu.tw 3a617090@gmail.com
2. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology
   Taichung 404, Taiwan
   jyjhang@nutc.edu.tw

Abstract

In this paper, a real-time navigation control system based on lidar sensing is proposed for use in unknown environments. The proposed system comprises a behavioral controller for controlling an autonomous Ackerman robot for obstacle avoidance in the absence of global map information when moving toward a goal. The adopted obstacle avoidance method is selected by a wall-following fuzzy controller. The input parameter of this controller is the distance between the robot and the wall, which is determined by the lidar sensor, and the output parameter of the controller is the steering angle of the robot for it to reach the destination without collision. To prevent the robot from entering an endless loop, an endless loop escape mechanism is added to the proposed system. The simulation and experimental results of this study indicate that the proposed navigation control system can effectively assist an Ackerman robot to complete the navigation task successfully in unknown environments.

Key words

Ackerman robot, fuzzy logic controller, lidar, navigation system, unknown environment

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS220826008L

Publication information

Volume 21, Issue 2 (April 2024)
Special Issue on Deep Learning Techniques in Intelligent Internet of Things and 5G Communication Networks
Year of Publication: 2024
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Lin, C., Jhang, J., Chuang, C.: Navigation Control of an Autonomous Ackerman Robot in Unknown Environments by Using a Lidar-Sensing-Based Fuzzy Controller. Computer Science and Information Systems, Vol. 21, No. 2, 473–490. (2024), https://doi.org/10.2298/CSIS220826008L