Title :
The obstacle avoidance planning of USV based on improved artificial potential field
Author :
Shaorong Xie ; Peng Wu ; Yan Peng ; Jun Luo ; Dong Qu ; Qingmei Li ; Gu, Jhen-Fong
Author_Institution :
Dept. of Mechatron. Eng., Shanghai Univ., Shanghai, China
Abstract :
The autonomous obstacle avoidance planning of USV is the guarantee and the precondition of carrying out the performance. Obstacle avoidance planning is required to possess high accuracy and instantaneity due to a complex environment and faster speed. The algorithm of Artificial Potential Field has the advantage of sample mathematical model, which is easy to understand and implement, and facilitate the underlying control. However, application of traditional Artificial Potential Field has the problems of local minimum, destination unreachable, and poor accuracy of algorithm. Aiming at these issues, a method of the obstacle avoidance planning of Unmanned Surface Vehicle based on improved Artificial Potential Field is proposed in this article, and its feasibility is demonstrated using MATLAB simulation.
Keywords :
collision avoidance; remotely operated vehicles; Matlab simulation; USV; improved artificial potential field; obstacle avoidance planning; unmanned surface vehicle; Collision avoidance; Convergence; Force; Mobile robots; Planning; Simulation; Artificial Potential Field; Unmanned Surface Vehicle; local minimum; obstacle avoidance planning;
Conference_Titel :
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location :
Hailar
DOI :
10.1109/ICInfA.2014.6932751