Real-time 3D path planning for sensor-based underwater robotics vehicles in unknown environment

Abstract

Studies path planning strategies on real-time 3D near-shortest path planning for sensor-based underwater robotics vehicles (URV) in an unknown environment. The unknown environment includes multiple static obstacles of arbitrary shape. Based on limited sensor vision zone and the URV attitude dynamics, a 3D near-shortest path planning algorithm is developed for the URV in an unknown environment. The control variables are a group of thrusters of the URV. This path planning algorithm incorporates the effects of vehicle mass point dynamics, body dynamic behavior, sensor vision zone, thruster characters and all environments. Software for the algorithm was developed to produce numerical solutions of path planning for the URV in different unknown environments. These numerical results of path planning include terrain following and terrain avoidance, avoiding static obstacles, passing some target points, and synthetic trajectory considering complex mazes. This algorithm can be generally used to online plan a path for any robot in an unknown environment.