RRT-based path planning with kinematic constraints of AUV in underwater structured environment

In this paper, we conduct Rapidly-exploring Random Trees(RRT)-based local path planning for an Autonomous Underwater Vehicle(AUV). RRT is a randomized sampling based data structure which can easily handle non-holonomic constraints such as kinematic model of the AUV. It is enable to solve the path planning problem efficiently in high-dimensional state space. We applied RRT to solve the local path planning problem of the AUV considering its kinematic model which has non-holonomic constraints. And then, the A* algorithm was used to find the shortest trajectory from the RRT which avoids obstacles in the known environment.