Voronoi-based adaptive area optimal coverage control for multiple manipulator systems with uncertain kinematics and dynamics

This paper studies an adaptive area optimal coverage control method for multi-manipulator systems under the presence of both uncertain kinematics and dynamics. Initially, an objective cost function associating the voronoi tessellation is utilized to transform the optimal coverage control into the tracking control problem. Consequently, an adaptive area optimal coverage control strategy is designed by using the adaptive dynamic and kinematic programming. In this control strategy, the sliding mode control technology for each robot manipulator system is created to pursue control optimality and prescribed coverage performance simultaneously. The adaptive control algorithm using the parameter linearization properties is further deployed to directly cope with the influence caused by the parameter uncertainties of manipulator dynamics and kinematics. Theoretical analysis is given to guarantee the stability and convergence of the proposed optimal area converge controller, subject to optimal cost. Illustrative example is provided to validate the performance of the proposed framework.