Mission-Oriented Gaussian Process Motion Planning for UUVs Over Complex Seafloor Terrain and Current Flows

Abstract

Wepresent a novel motion planning framework for unmanned underwater vehicles (UUVs) - the first framework that applies Gaussian process motion planning to solve a 3D path planning problem for a 6-DoF robot in underwater environments. We address missions requiring UUVs to remain in close proximity to seafloor terrain, which must be achieved alongside collision avoidance. Our framework also considers the influence of current flows as part of the cost function, allowing for more accurate planning. To evaluate the performance of our proposed framework, we compare it with the widely used RRT* and STOMP algorithms over a range of underwater environments. Our experimental results demonstrate the stability and time efficiency of our framework.