DocumentCode :
154478
Title :
A considering lane information and obstacle-avoidance motion planning approach
Author :
Yun-xiao Shan ; Bi-jun Li ; Xiaomin Guo ; Jian Zhou ; Ling Zheng
Author_Institution :
State Key Lab. of Inf. Eng. in Surveying Mapping & Remote Sensing, Wuhan Univ., Wuhan, China
fYear :
2014
fDate :
8-11 Oct. 2014
Firstpage :
16
Lastpage :
21
Abstract :
We present an improved RRT* to blend lane information and avoid obstacles in this paper. Unlike most of other improved RRT*, this paper attach great importance to the convergent goal of RRT*. We consider the condition that there exists a reference path, maybe not the shortest path, but the environment requires the vehicle to follow, such as a lane center. Compared with standard RRT* applied to differential situation, we first add a TesttoGoal procedure to improve the convergent speed and also make sure the path can reach the goal pose but not the goal region to promise the safety of autonomous vehicle. One of the key characteristic of our improved algorithm is to employ a fast clothoid fitting method into RRT* to enable us to control the curvature. Another important modification is the heuristic sampling method that makes our algorithm can converge to lane center. We evaluate our algorithm with a real lane to demonstrate the effect of our modifications.
Keywords :
collision avoidance; mobile robots; sampling methods; trees (mathematics); TesttoGoal procedure; autonomous vehicle; blend lane information; convergent speed; differential situation; fast clothoid fitting method; goal region; heuristic sampling method; improved RRT*; lane center; obstacle-avoidance motion planning approach; rapidly-exploring randomized tree; reference path; Conferences; Heuristic algorithms; Planning; Robots; Safety; Standards; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
Conference_Location :
Qingdao
Type :
conf
DOI :
10.1109/ITSC.2014.6957659
Filename :
6957659
Link To Document :
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