Control Barrier Function Based Visual Servoing for Underwater Vehicle Manipulator Systems under Operational Constraints.

This paper presents a novel control strategy for image-based visual servoing (IBVS) of underwater vehicle manipulator systems (UVMS) using control barrier functions (CBFs) to handle field of view (FoV) constraints and system's operational limitations such as manipulator joint limits and vehicle velocity performances. The proposed approach combines the advantages of IBVS, which provides visual feedback for control, with CBFs, which can formally enforce visibility and safety constraints on the UVMS's motion. A CBF-based control law is derived and integrated with the IBVS algorithm, which guarantees the satisfaction of FoV and system's operational constraints and ensure stability of the closed-loop system. To deal with FoV constraints, the proposed method uses a FoV index to estimate the degree of visibility of the scene, which is used to adjust the control inputs accordingly. The effectiveness of the proposed strategy is demonstrated through realistic simulation results, showing improved performance and safety of the UVMS under FoV and operational constraints compared to traditional IBVS methods. The results indicate that the proposed approach can handle the challenging underwater environment, UVMS dynamics and the operational constraints effectively, making it a valuable control strategy for practical applications of UVMS.