Forward-Looking Sonar-Based Stream Function Algorithm for Obstacle Avoidance in Autonomous Underwater Vehicles

Abstract

Autonomous Underwater Vehicles (AUVs) have emerged as pivotal tools for intricate underwater missions, spanning seafloor exploration to meticulous inspection of subsea infrastructures such as pipelines and cables. Although terrestrial obstacle avoidance paradigms exhibit proficiency, their efficacy diminishes in aquatic environments due to the nuanced challenges and distinct dynamics inherent to marine realms and AUV maneuvering. This paper presents an advanced obstacle avoidance algorithm for AUVs based on a stream function framework. Central to this approach is the utilization of a stream function, further nuanced by a radial histogram that serves as the defining cost function. This work also encapsulates constraints related to the maximum allowed path curvature, ensuring enhanced path optimization. Comprehensive simulation results validate the robustness and adaptability of the introduced strategy, evincing its capacity to outline both practicable and optimal evasion trajectories across diverse operational contexts.