A Switching Nonlinear Model Predictive Control Strategy for Safe Collision Handling by an Underwater Vehicle-Manipulator System

Abstract

For active intervention tasks in underwater environments, the use of autonomous vehicles is just now emerging as an active area of research. During operation, for various reasons, the robot might find itself on a collision course with an obstacle in its environment. In this paper, a switching Nonlinear Model Predictive Control (NMPC) strategy is proposed to safely handle collisions for an Underwater Vehicle-Manipulator System (UVMS). When avoiding the collision is impossible, the control algorithm takes advantage of the manipulator, using it to push against the obstacle, and deflect away from the collision. Virtual experiments are performed to demonstrate the algorithm's capability to successfully detect collisions and either avoid them, or use the manipulator to handle them appropriately without damaging sensitive areas of the vehicle.

This work has been submitted to the 2026 Mediterranean Conference on Control and Automation (MED) to be considered for publication. Figures and animations are available at https://zenodo.org/records/18357280