Improved RRT Algorithm for AUV Target Search in Unknown 3D Environment

Due to the complexity of the marine environment, underwater target search and interception is one of the biggest problems faced by an autonomous underwater vehicle (AUV). At present, there is quite a lot of research in terms of the two-dimensional environment. This paper proposes an improved rapidly exploring random trees (RRT) algorithm to solve the problem of target search and interception in an unknown three-dimensional (3D) environment. The RRT algorithm is combined with rolling planning and node screening to realize path planning in an unknown environment, and then the improved RRT algorithm is applied to the search and interception process in a 3D environment. Combined with the search decision function and the three-point numerical differential prediction method, the RRT algorithm can search for and effectively intercept the target. Numerical simulations in various situations show the superior performance, in terms of time and accuracy, of the proposed approach.

Automated summary

This paper proposes an improved rapidly exploring random trees (RRT) algorithm to solve the problem of target search and interception in an unknown three-dimensional environment. The algorithm combines rolling planning and node screening for path planning in the unknown environment, and utilizes a search decision function and numerical differential prediction method for target search and interception.