Abstract
Autonomous operation in underwater environments is, arguably, one of the most complex domains. It requires safe operations under the presence of unpredictable surge, currents, uncertainty, and dynamic obstacles that challenges to the highest degree real-time motion planning; the primary focus of this paper. Although previous work addressed the problem of safe real-time 3D navigation in cluttered underwater environments, it did not account explicitly for disturbances, currents, dynamic obstacles, or uncertainty growth. This paper presents ResiPlan, a novel motion planning framework that utilizes past information of errors monitoring the path follower’s performance, along with estimation of dynamic obstacles and uncertainty, to produce adaptive paths by adjusting the safety margins accordingly. Extensive numerical experiments and simulations validate the safety guarantees of the technique, in a variety of different environments with various types of disturbance, showcasing the strong potential to be utilized for operations in challenging underwater environments.
