Aiming at the path planning problem of unmanned surface vehicle(USV)in unknown environment,an improved rapid-ly-exploring random tree artificial potential field path planning algorithm(IRRT*-APF)considering the kinematics constraints of USV is proposed.The improved artificial potential field(APF)method is introduced to improve the obstacle avoidance perfor-mance of the rapidly-exploring random tree(RRT*).The use of the taxicab geometry method greatly improves the efficiency of the RRT*algorithm.The proposed IRRT*-APF method is compared with the rolling RRT*algorithm and PSOFS algorithm in simulation experiments,and the results show that the number of turns and corners planned by the proposed method are signifi-cantly reduced,which is conducive to the smooth control of the USV.At the same time,it reduces the time for planning the path.Further simulation experiments in the wind and waves interference environment are carried out,and the results show that the pro-posed algorithm can still plan the trajectory consistent with the kinematics constraints of USV even in the case of wind and waves interference,which shows strong robustness against wind and waves.
Unmanned surface vehicleRapid-exploration random treeArtificial potential fieldLocal path planningRolling win-dow
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