Title: Advances on a Null-space-based Approach to Range-only Underwater Steering and Positioning
Author(s): Daniela De Palma, Giovanni Indiveri, António M. Pascoal
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 472 - 479
Cite this article: De Palma, Daniela, Indiveri, Giovanni, Pascoal, António M., "Advances on a Null-space-based Approach to Range-only Underwater Steering and Positioning," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 472-479.
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In
Abstract: This paper addresses the problem of optimal AUV (Autonomous Underwater Vehicle) motion generation to maximise the range-related information available for vehicle positioning subject to the condition that the overall trajectory will drive the vehicle from an initial to a final target point. To this end we resort to a task prioritisation technique using a nullspace-based projection approach. This allows decoupling the motion objectives from those of maximising an observability based criterion. Preliminary results on this topic have been presented in previous work. Here, a careful singularity analysis of the null space projector operator is formalized and discussed. A saturation management algorithm that copes with vehicle velocity command saturation by properly assigning the velocity vector to the two tasks is also proposed. The stability of the resulting control law is analysed using a Lyapunov-based approach. Robustness against uncertainty in the initial position of the vehicle is also handled by comparing two alternative procedures: the first aims at optimising the worst case scenario, that is, maximising the minimum of the observability metric inside the uncertainty region; the second, a novel approach, aims at optimising the most frequent observability metric inside the uncertainty region. The work is completed by combining the guidance algorithm with an observer for the estimation of the vehicle’s position and its associated uncertainty. Results of numerical simulations show the effectiveness of the proposed strategy.