An Online Motion Planning Framework for Navigating Torpedo-shaped Autonomous Underwater Vehicles in Unknown Underwater Environments

Abstract

Navigating unknown underwater environments is a significant challenge for autonomous underwater vehicles (AUVs), especially those with torpedo-like shapes. Lacking a prior map, these vehicles rely on real-time sensor data for perception. Although online motion planning addresses this challenge, many existing methods are primarily tested on more maneuverable robots, such as multicopters and ground vehicles, and do not account for the unique kinematics of torpedo-shaped AUVs, such as limited lateral movement, or the need for 3D motion planning. In this paper, we propose an online motion planning system specifically designed for torpedo-shaped AUVs to navigate 3D underwater terrain without prior environmental knowledge. The system employs a receding horizon planning framework to ensure safe navigation by replanning the trajectory when collisions are detected or the planning horizon is reached. For trajectory generation, a search-based method is used and utilizes a 3D Dubins curve heuristic to guide the generation of an optimal 3D trajectory that adheres to the AUV’s kinematic constraints. To further enhance safety and smoothness, gradient-based optimization is applied to refine the trajectory. Experiments in simulated environments validate the proposed method, demonstrating its ability to generate safe trajectories for AUVs in complex and unknown environments. We release our code as an open-source package<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>.