DocumentCode :
176138
Title :
Variable probability based bidirectional RRT algorithm for UAV path planning
Author :
Wu Xinggang ; Guo Cong ; Li Yibo
Author_Institution :
Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
fYear :
2014
fDate :
May 31 2014-June 2 2014
Firstpage :
2217
Lastpage :
2222
Abstract :
Since the traditional rapidly-exploring random tree connect (RRT-connect) algorithm cannot be applied to the problem of unmanned aerial vehicle (UAV) path planning directly, a variable probability based bidirectional RRT algorithm (VPB-RRT) is proposed. The restriction of the turning angle of UAV is joined in the process of generating random points of the programming algorithm, which makes the performance of the track satisfy the conditions for flight. By using this algorithm to identify the probability though rasterizing the planning space and importing the concept of coverage rate, track has been made to satisfy the respects of online time and accuracy of UAV path planning. Compared with the A* algorithm, traditional RRT algorithm and RRT-connect algorithm, the results show that VPB-RRT fully satisfies the requirements of online UAV path planning which with shorter time and higher accuracy.
Keywords :
autonomous aerial vehicles; path planning; probability; trees (mathematics); RRT-connect algorithm; VPB-RRT; coverage rate; flight conditions; online UAV path planning; planning space; programming algorithm; random points generation; rapidly-exploring random tree connect algorithm; track performance; turning angle restriction; unmanned aerial vehicle path planning; variable probability based bidirectional RRT algorithm; Educational institutions; Heuristic algorithms; Path planning; Planning; Programming; Turning; Vectors; Coverage Rate; RRT-connect Algorithm; Restriction; UAV Path Planning; Variable Probability Based Bidirectional RRT Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
Type :
conf
DOI :
10.1109/CCDC.2014.6852537
Filename :
6852537
Link To Document :
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