An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

被引:56
作者
Ayawli, Ben Beklisi Kwame [1 ,2 ]
Chellali, Ryad [3 ,4 ]
Appiah, Albert Yaw [1 ,5 ]
Kyeremeh, Frimpong [1 ,5 ]
机构
[1] Nanjing Tech Univ, Coll Elect Engn & Control Sci, Nanjing, Jiangsu, Peoples R China
[2] Sunyani Tech Univ, Comp Sci Dept, Sunyani, Ghana
[3] Nanjing Forestry Univ, Nanjing, Jiangsu, Peoples R China
[4] Kita Technol, Nanjing, Jiangsu, Peoples R China
[5] Sunyani Tech Univ, Elect & Elect Engn Dept, Sunyani, Ghana
关键词
MOBILE-ROBOT NAVIGATION; DYNAMIC WINDOW APPROACH; PARTICLE SWARM OPTIMIZATION; ANT COLONY OPTIMIZATION; NEURO-FUZZY CONTROLLER; POTENTIAL-FIELD METHOD; OBSTACLE AVOIDANCE; MOVING OBSTACLES; SYSTEM; ALGORITHM;
D O I
10.1155/2018/8269698
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.
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页数:27
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