Unmanned Surface Vehicles(USV) path planning has important application value in the field of autonomous navigation. In order to plan a path with simple calculation, less time consumption and low complexity, an improved Probabilistic Roadmap(PRM) algorithm based on USV path planning is proposed. The randomly generated sampling points in the traditional PRM algorithm results in high computational complexity and insufficient flexibility and smoothness in the planned path. In order to optimize the generation strategy of sampling points and improve the smoothness of the path, the boundary box analysis technology and Catmull-Rom Spline interpolation of the path are introduced into the PRM algorithm to obtain I-NPRM algorithm. Using three different path planning schemes for simple, complex and special water environments and comparing them with the planning effectiveness of I-NPRM algorithm, NPRM algorithm, PRM algorithm and A* algorithm under three indicators of runtime, path length and number of inflection points. The experimental results indicate that the I-NPRM algorithm can optimize the sampling point generation strategy while reducing runtime and path length, as well as reducing the number of inflection points. The planned path has high smoothness, which is more in line with the motion constraints and maneuverability of the USV and improves the safety and stability of the autonomous navigation system
In order to improve the safety of Unmanned Surface Vessel (USV) sailing in the ocean with movable obstacles, a new method based on greedy algorithm, ant colony algorithm and grid method is proposed. By adding periodic repeated calculation of movable obstacles with known paths, the route is periodically replanned. The approximation method is used to solve the problem that the traditional greedy ant colony algorithm is difficult to avoid the movable obstacles in the optimal course design of unmanned surface vessel. The algorithm uses greedy algorithm to plan the optimal route and ant colony algorithm to get rid of the situation that greedy algorithm is easy to enter the local convergence state. By rationalizing the movable obstacles on the known path, the navigation water limit of unmanned surface vessel caused by movable obstacles is avoided. The simulation results show that the algorithm is practical and reasonable for optimal route design when USV avoids movable obstacles. The simulation results show that the algorithm has the disadvantage of long search time.
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