Autonomous navigation and active perception with complex articulated AUVs

Abstract

With the recent progress in underwater robotics, autonomous underwater vehicles (AUVs) are increasing their mission capacity and range of applications operating in proximity to underwater infrastructure and closer to the wave zone for data collection and environmental monitoring. Future applications will necessitate more complex articulated systems that will be tasked to operate with increased safety, efficiency, and capacity. In this article, we present a novel motion planning framework for enabling, for the first time, safe autonomous navigation and active perception in high-dimensional articulated AUVs, employed with multiple arbitrary-configured sensors, in complex dynamic environments that are prone to uncertainties, disturbances, and currents. Inspired by previous work, we expand on a locally optimal and empirically safe pipeline designed for holonomic AUVs and enable it to handle articulated AUVs with potentially non-trivial dynamics that are unknown to the planner. We test the proposed methodologies with challenging simulated cases using an underwater snake robot (USR) with realistic dynamics and a generic underwater vehicle-manipulator system (UVMS) comprising of a holonomic base employed with a manipulator. Our results showcase the effectiveness of the proposed technique in producing efficient and safe real-time solutions, while discussing current limitations, computational bottlenecks, and potential solutions.