Collision-free path planning for unmanned surface vehicle by using advanced A algorithm

In recent years, the development of autonomous surface vehicles has been an area of increasing research interest. The presented study focuses on two objectives: the path planning for unmanned surface vehicle (USV) and the design of fuzzy logical controller of USV. Path planning is an essential topic of robotics, and the main purpose in this investigation is to determine approximately the safest and shortest path. A*algorithm is the most commonly used for path finding, but the paths found by A*are not truly the shortest paths because the potential headings of the paths are artificially constrained. To tackle this shortcoming, the Finite Angle A*(FAA*) method is proposed in this study. The experimental results show that FAA*finds shorter paths than both A*on grids and A*with the post-smoothed method. To find a safer path that is as short as possible is our primary goal. The modified definition of line-of-sight is proposed to achieve this objective by adding a variable called safe distance to the line-of-sight formula, and the value of the variable can be decided by its users. The image analysis is utilized to convert color satellite images into binary images which can be used as the maps of FAA*. This procedure can reduce the cost of creating maps for USV. In this article, fuzzy logic navigation is presented. The fuzzy controller of USV is designed to automatically control two DC brush thrusters. Finally, the USV trial is successfully completed in Anping harbor, and the experimental results illustrate that the USV can autonomously cruise along the path found by FAA*.