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

TL;DR

This paper introduces a switching NMPC strategy for underwater vehicle-manipulator systems that ensures safety during collisions by either avoiding obstacles or using the manipulator to deflect away, demonstrated through virtual experiments.

Contribution

It presents a novel control approach combining collision detection and handling for UVMS, enabling safe operation in complex underwater environments.

Findings

Successfully detects and avoids collisions in simulations

Uses manipulator to deflect and handle unavoidable collisions

Demonstrates effectiveness through virtual experiments

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.