A Model Predictive Control Approach to Enhance Obstacle Avoidance While Performing Autonomous Docking

In the present paper, we propose a control approach to perform docking of an autonomous surface vehicle (ASV) while avoiding surrounding obstacles. This control architecture is composed of two sequential controllers. The first outputs a feasible trajectory between the vessel's initial and target state while avoiding obstacles. This trajectory also minimizes the vehicle velocity while performing the maneuvers to increase the safety of onboard passengers. The second controller performs trajectory tracking while accounting for the actuator's physical limits (extreme actuation values and the rate of change). The method's performance is tested on simulation, as it enables a reliable ground truth method to validate the control architecture proposed.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/oceans55160.2024.10753848
Primary Topic
Aerospace Engineering and Energy Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

A Model Predictive Control Approach to Enhance Obstacle Avoidance While Performing Autonomous Docking

Salviano Soares, Nuno Cruz, Bruno M. Ferreira, A. Pinto et al.
Aerospace Engineering and Energy Systems
article

A Model Predictive Control Approach to Enhance Obstacle Avoidance While Performing Autonomous Docking

Salviano Soares, Nuno Cruz, Bruno M. Ferreira, A. Pinto, J. Cunha
article en

Abstract

In the present paper, we propose a control approach to perform docking of an autonomous surface vehicle (ASV) while avoiding surrounding obstacles. This control architecture is composed of two sequential controllers. The first outputs a feasible trajectory between the vessel's initial and target state while avoiding obstacles. This trajectory also minimizes the vehicle velocity while performing the maneuvers to increase the safety of onboard passengers. The second controller performs trajectory tracking while accounting for the actuator's physical limits (extreme actuation values and the rate of change). The method's performance is tested on simulation, as it enables a reliable ground truth method to validate the control architecture proposed.

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Aerospace Engineering and Energy Systems
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A Model Predictive Control Approach to Enhance Obstacle Avoidance While Performing Autonomous Docking — Salviano Soares, Nuno Cruz, et al. · (2024) | TGRS Research Map | TGRS