Research On Path Planning Of USV Based On Electronic Chart And Radar Image

Unmanned Surface Vehicle(USV)is increasingly attracting the attention of various countries as tools for monitoring marine environment,maintain the marine rights and interests and modern weapons.And path planning is one of the key technologies for USV to realize autonomous navigation and collision avoidance decision-making which involves the perception of static and dynamic environment.This thesis gives a kind of collision avoidance decision-making and then a feasible path for USV is given based on the information fusion of static environment of USV sailing area which is obtained by electronic chart and dynamic environment of USV around which is obtained using radar perception.In this thesis an electronic chart is considered as a reference map and a radar image is considered as a real-time map.The radar image will be scaled at a certain scale and rotated.The canny algorithm is used for edge detection of radar images and electronic chart which have been processed and then the kittler algorithm is used for binarization processing.Finally the information fusion of electronic and radar image is realized by overlay the radar image to electronic chart according to best matching points by the means of Hausdorff similarity match algorithm.An environmental information simulation model of USV is established according to the environmental information of electronic chart after approximating the irregular obstacles for circle.This thesis chose artificial potential field method as the path planning algorithm which has a faster computational speed and improves the disadvantage of artificial potential field method after several common local path planning algorithm are compared.And a simulation experiment is also carried out in this thesis and the simulation results verified the feasibility and effectiveness of USV path planning based on electronic chart and marine radar which has certain reference significance for the research and implementation of USV collision avoidance decision-making.