Genetic Algorithm based Obstacle Avoidance for 4-Wheeled Robot

被引:1
|
作者
Kim, Junmyeong [1 ]
Kim, Kwanho [1 ]
Jo, Kanghyun [1 ]
机构
[1] Univ Ulsan, Dept Elect Elect & Comp Engn, Ulsan, South Korea
来源
2023 62ND ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS, SICE | 2023年
基金
新加坡国家研究基金会;
关键词
Robotic and Automation Systems; Intelligent Control; Adaptive and Optimal Control;
D O I
10.23919/SICE59929.2023.10354237
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes an algorithm that uses for decision-making and control in Autonomous Mobile Robots (AMR) and performs in a virtual environment for simulation. In the decision-making stage, the algorithm uses the Velocity Obstacle (VO) and Artificial Potential Field (APF) methods to select the optimal velocity for avoiding collision and reaching the goal point in real-time. It additionally computes fitness that helps eliminates rapid changes in velocity. In control, the PID controller moves the robot along the velocity determined in the decision-making stage. The PID gain is updated by the gradient descent method to find the optimal gains. Proper brake torque is applied for the robot moves smoothly according to velocity previously determined. This parameter, alpha affects chance of avoidance obstacles, however it increase the travel time in experiment. The travel time averagely increase 9.54% at every alpha 0.1. When comparing the smallest and largest periods, the larger period resulted in a 29.9% decrease in control error. The results also showed that using the proposed PID controller resulted in a 13.6% decrease in control error compared to using a fixed PID controller.
引用
收藏
页码:297 / 300
页数:4
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