Autonomous obstacle avoidance strategy for mobile robots in indoor dynamic environment

被引：0

作者：

Yang M. ^{[1
]}

Wu Y. ^{[1
]}

Zhang Y. ^{[1
]}

Xiao X. ^{[1
]}

机构：

[1] School of Power and Mechanical Engineering, Wuhan University, Wuhan

来源：

Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2019年 / 50卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Autonomous obstacle avoidance; Dynamic obstacles; Fuzzy neural network; Mobile robot; Sub-target point updating strategy;

D O I：

10.11817/j.issn.1672-7207.2019.08.010

中图分类号：

学科分类号：

摘要：

Aiming at the problem of autonomous obstacle avoidance for mobile robots in unknown indoor dynamic environment, an adaptive fuzzy neural network optimization obstacle avoidance algorithm was proposed, which integrates the dynamic obstacle direction judgment strategy and the sub-target point updating strategy. The obstacle avoidance control system of mobile robots was designed based on this algorithm. Firstly, the motion model of mobile robot was analyzed to obtain the target angle of the robot. Then, the distance information of obstacles was obtained by ultrasonic sensor, and the moving direction of dynamic obstacles was judged by the distance information of obstacles. The sub-target points were thus updated. Finally, the steering angle and speed of the robot were displayed in real time by using adaptive fuzzy neural inference system. The robot's steering angle was controlled to reach the target point without collision. The results show that the proposed algorithm enables mobile robots to recognize obstacles and judge the motion direction of dynamic obstacles in an unknown dynamic environment to achieve autonomous obstacle avoidance. Compared with the strategy of no sub-target point updating, the average moving speed of mobile robots is increased by 11.75%, which verifies the effectiveness of the proposed algorithm. © 2019, Central South University Press. All right reserved.

引用

页码：1833 / 1839

页数：6

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