Dynamic Obstacle Avoidance for AUV based on the Randomized Samplingbased Algorithm

Realtime dynamic obstacles avoidance in the preunknown environment is stateoftheart in the autonomous underwater vehicle path planning. In this paper, the Local Realtime Reactive Randomized SamplingBased Tree (LR3SBT) is proposed. The LR3SBT considers various obstacles and applied the RRT algorithm to generate the collisionfree path in the timevarying environment. The LR3SBT consists of four components: 1 SamplingBased Tree path planner (SBTPP), 2 Local path planner (LPP), 3 Reactive path planner (RPP), and 4 Critical path planner (CPP). The initial path is designed by offspring random nodes through the SBTPP. If unknown obstacles are detected in the initially planned path, the LPP is called by LR3SBT. The RPP module is called if the desired path does not generate through the LPP. If unknown dynamic obstacles are detected, the CPP module is called. The planned path is optimized eliminating further nodes using the concept of triangular inequality. Simulation results demonstrate the path planning and dynamic obstacle avoidance in the preunknown environment through the LR3SBT. The realtime response and certain obstacles avoidance are two characteristics of the LR3SBT method.