Path planning and obstacle avoidance for mobile robots in a dynamic environment

被引：0

作者：

Sun, Liping ^{[1
]}

Luo, Yonglong ^{[1
]}

Ding, Xintao ^{[1
]}

Wu, Longlong ^{[1
]}

机构：

[1] College of National Territorial Resources and Tourism, Anhui Normal University, Wuhu

来源：

Open Automation and Control Systems Journal | 2014年 / 6卷 / 01期

基金：

中国国家自然科学基金;

关键词：

BP neural networks; Dynamic environment; Obstacle avoidance; Path planning;

D O I：

10.2174/1874444301406010077

中图分类号：

学科分类号：

摘要：

Because traditional obstacle avoidance path planning methods have a lot of problems, such as large amount of calculation, low efficiency, poor optimization capability, and lack of dealing with dynamic obstacles, a new method which implements real-time path planning of mobile robot is presented. The method builds a neural network model for the robot workspace, and then it uses the model to obtain the relationship between the dynamic obstacles and the network output. It can choose the local optimal collision-free path by the path planning in a dynamic environment (PPIDE) algorithm to find the path between two points for dealing with obstacles. The proposed method is suitable for dynamic environment where both linear and planar obstacles exist. Simulation results prove its effectiveness. © Sun et al.; Licensee Bentham Open.

引用

页码：77 / 83

页数：6

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