Path Planning for Smart Car Based on Dijkstra Algorithm and Dynamic Window Approach

被引：66

作者：

Liu, Li-sang ^{[1
,2
,3
,4
]}

Lin, Jia-feng ^{[1
]}

Yao, Jin-xin ^{[1
,3
]}

He, Dong-wei ^{[1
,2
]}

Zheng, Ji-shi ^{[1
,4
]}

Huang, Jing ^{[1
,3
]}

Shi, Peng ^{[1
,5
]}

机构：

[1] Fujian Univ Technol, Sch Elect Elect Engn & Phys, Fuzhou 350118, Peoples R China

[2] Fujian Univ Technol, Fujian Key Lab AED, Fuzhou 350118, Peoples R China

[3] Fujian Univ Technol, Natl Demonstrat Ctr Expt Elect Informat & Elect T, Fuzhou 350118, Peoples R China

[4] Univ Essex, Sch Comp Sci & Elect Engn, Wivenhoe Pk, Colchester CO4 3SQ, Essex, England

[5] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia

来源：

WIRELESS COMMUNICATIONS & MOBILE COMPUTING | 2021年 / 2021卷

关键词：

Autonomous driving - Avoid obstacles - Depth information - Dijkstra algorithms - Dynamic window approach - Global path planning - Indoor environment - Local path-planning;

D O I：

10.1155/2021/8881684

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

引用

页数：12

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