Image Based Visual Servoing for Floating Base Mobile Manipulator Systems with Prescribed Performance under Operational Constraints

This paper presents a novel Image-Based Visual Servoing (IBVS) control approach for Floating Base Mobile Manipulator Systems (FBMMSs) that imposes prescribed transient and steady-state response on the image feature coordinate errors while satisfying the visibility constraints that arise owing to the camera’s limited field of view. The proposed control strategy does not incorporate any knowledge on either the FBMMS dynamic model, the exogenous disturbances, or the inevitable camera calibration and depth measurement errors. More specifically, it guarantees: (i) predefined behavior in terms of overshoot, convergence rate, and maximum steady-state error value of the image features and system velocities tracking errors; (ii) satisfaction of camera field of view constraints; (iii) bounded closed-loop control signals, and (iv) reduced design and implementation complexity. Additionally, the performance of the developed scheme is solely determined by certain designer-specified performance functions/parameters, and it is fully decoupled by the control gains selection. The efficiency of the proposed scheme is demonstrated via a realistic simulation study, using an eye-in-hand Underwater Vehicle Manipulator System (UVMS) as a test-bed FBMMS platform.