An optimization-based approach for design and analysis of stable 2.5D visual servoing under sensor and actuator constraints

In this paper, a 2.5D visual servoing controller is proposed that utilizes a Lyapunov based design method to drive the robot pose to a setpoint while satisfying constraints related to limited camera field-of-view and size of actuation. A nominal feedback controller is first introduced which is then modified through an optimization approach in order to satisfy the motion constraints. In the absence of actuator constraints, the proposed control law yields a semi-global asymptotic (exponential) stability result via a Lyapunov analysis. When actuator constraints are introduced, the result is local asymptotic stability with known bounds on the region of attraction. Simulation results demonstrate the efficacy of the optimized visual servoing control strategy.