Open AccessLocal path planning for unmanned surface vehicle with improved artificial potential field method
Author(s) -
Xiao Ma,
Lin Zuan,
Ruiyin Song
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012125
Subject(s) - potential field , obstacle , gravitational potential , motion planning , potential energy , gravitational field , field (mathematics) , position (finance) , unmanned surface vehicle , computer science , control theory (sociology) , gravitation , artificial intelligence , robot , physics , mathematics , classical mechanics , engineering , marine engineering , control (management) , finance , geophysics , pure mathematics , political science , law , economics
Aiming at the drawbacks of traditional artificial potential field method in local path planning for USV (unmanned surface vehicle), an improved artificial potential field method is proposed. By improving the gravitational potential field model and restraining the distant gravitational potential field, the problem of USV colliding with obstacles is solved. In the repulsion field model, the influence factors such as relative position and relative velocity are introduced to reduce the repulsion potential field intensity of the obstacle near the target, so as to solve the problem of goal nonreachable with obstacle nearby. The regulation mechanism of random perturbation potential energy is introduced to solve the problem that it is difficult to move at local minimum points. The rationality and superiority of the proposed improved artificial potential field method are verified by simulation and comparison experiments.