Work

Hierarchical Flocking Control Strategy for Underactuated Autonomous Surface Vehicles with Integrated Obstacle Avoidance

Year: 2025

Type: article

Abstract: This paper introduces a hierarchical flocking control strategy for underactuated autonomous surface vehicles addressing nonlinear dynamics, environmental disturbances, and obstacle avoidance. The proposed framework integrates high-level flocking, mid-level path-following guidance, and low-level dynamic control that explicitly manages actuator saturation. This hierarchical framework ensures cohesive group behavior, smooth transitions between control layers, and bounded control actions. Simulations using the CyberShip II model validate effectiveness, demonstrating minimized tracking errors and successful collision avoidance. The results highlight the robustness and applicability of the proposed approach for coordinating multiple underactuated autonomous surface vehicles in realistic operational scenarios with constrained propeller power.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.07.020

Authors: Thalia Morel, Federico Peralta, Yan Chen, Guillermo Bejarano, Luis Orihuela

Institutions: Universidad Loyola Andalucía, Arizona State University, Universidad de Huelva

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Agencia Estatal de Investigación

Awards: G1777124376, G7305548598