Real Time Underwater Obstacle Avoidance and Path Re-planning Using Simulated Multi-beam Forward Looking Sonar Images for Autonomous Surface Vehicle

Abstract

This paper describes underwater obstacle avoidance and path re-planning techniques for autonomous surface vehicle (ASV) based on simulated multi-beam forward looking sonar images. The sonar image is first simulated and then a circular obstacle is defined and created in the field of view of the sonar. In this study, the robust real-time path re-planning algorithm based on an A* algorithm is developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames with a proper update frequency between the start point and the goal point both in static and dynamical environments. The performance of proposed method is verified through simulations, and tank experiments using an actual ASV. While the simulation results are successful, the vehicle model can avoid both single obstacle, multiple obstacles and moving obstacle with the optimal trajectory. For tank experiments, the proposed method for underwater obstacle avoidance system is implemented with the ASV test platform. The vehicle is controlled in real-time and moderately succeeds in its avoidance against the obstacle simulated in the field of view of the sonar together with the proposed position stochastic estimation of the vehicle.