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This paper presents a novel control framework for underwater robot formations that relies entirely on vision-based sensing without requiring communication links. By integrating barrier Lyapunov functions with command-filtered backstepping, the method effectively handles actuator saturation and collision avoidance within second-order vehicle dynamics. The approach is validated through Software-in-the-Loop simulations, offering a robust solution for autonomous marine robotics where traditional communication infrastructure is unavailable.
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Vision-based Underwater Formation Control With Input Saturations via Barrier Lyapunov Functions

arXiv1 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.25917v1 Announce Type: new Abstract: In this work, we propose a communication-free framework for vision-based formation control of fully actuated underwater robots subject to sensing constraints, collision-avoidance requirements, and input saturations. Recentered barrier Lyapunov functions encode sensing and collision-avoidance constraints, while command-filtered backstepping extends the design to the second-order vehicle dynamics. The resulting control objective is enforced through a quadratic program that explicitly accounts for actuator limits. Conservative sensing domains provide margins from the physical limits and are adaptively relaxed when necessary, allowing temporary violation of the conservative bounds. The proposed approach is validated through realistic Software-in-the-Loop (SITL) simulations in Gazebo.

Abstract:In this work, we propose a communication-free framework for vision-based formation control of fully actuated underwater robots subject to sensing constraints, collision-avoidance requirements, and input saturations. Recentered barrier Lyapunov functions encode sensing and collision-avoidance constraints, while command-filtered backstepping extends the design to the second-order vehicle dynamics. The resulting control objective is enforced through a quadratic program that explicitly accounts for actuator limits. Conservative sensing domains provide margins from the physical limits and are adaptively relaxed when necessary, allowing temporary violation of the conservative bounds. The proposed approach is validated through realistic Software-in-the-Loop (SITL) simulations in Gazebo.

Robotics (cs.RO); Systems and Control (eess.SY)

arXiv:2609.25917 [cs.RO]

(or arXiv:2609.25917v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.25917 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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