Application of search algorithms in unmanned surface vehicle track planning

  Objectives  There is now an increasing interest in deploying unmanned vehicles (USVs) to support complex oceanic operations. In order to perform these tasks more efficiently, a reliable track planning algorithm is required. Based on the research of existing path planning algorithms, a search scanning algorithm based on 2D scanning idea is proposed.

  Methods  First, establish an environmental space model. On the premise that there is an obstacle between the starting point and the end point, the surrounding obstacle information is acquired through the 360° scan of the starting point, and the child nodes are determined. The acquisition sub-node is determined by the cost function, and the optimal sub-node continuously scans and updates the next-generation sub-node to scan to the end point, and finally determines the planned route. Experiments were performed using the LabView2017 platform to write algorithm simulation software.

  Results  The results showed that the search scan algorithm is of a higher quality on the planned path than the ant colony algorithm.

  Conclusions  The search algorithm reduces the problem that the result is not the optimal solution in the traditional algorithm planning path, and effectively improves the reliability of the algorithm applied to the two-dimensional space path planning.