Mobile Robot Path Planning in Complicated Environment

被引：0
|
作者：
Pan, Hu [1 ]
Guo, Chen [1 ]
Wang, Zhaodong [1 ]
机构：
[1] Dalian Martime Univ, Dalian 116026, Peoples R China
来源：
2018 13TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2018年
基金：
中国国家自然科学基金;
关键词：
OBSTACLE AVOIDANCE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The function of potential field in the traditional artificial potential field method only contains the position distance information, it can only deal with the path planning in static environment. By modifying the potential field, the velocity and acceleration information are introduced into the function of potential field to make the robot can avoid dynamic obstacle. In addition, taking into account the large number of static and dynamic obstacles in complex environment, A* algorithm is used to obtain the global sub-target points to guide the robot path planning. Simulation results show that the improved artificial potential field method can not only avoid dynamic obstacles but also get the optimized path.
引用
收藏
页码：474 / 478
页数：5
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