Error regulation strategies for Model Based visual servoing tasks: Application to autonomous object grasping with Nao robot

When applying service robotic tasks using sensor based control, a classical exponential decrease of the error is usually used in the control laws which can reduces the performance of the executed task. In fact, due to this choice, the convergence time greatly increases especially at the end of the process. To ameliorate the performance of such tasks, we present in this paper two new error regulation strategies to accelerate the service tasks execution. These propositions are compared with the classical one in the case of performing autonomous object's manipulation tasks using real-time visual servoing. The Model Based Tracking method is used to apply head servoing and grasping of different objects using Nao humanoid robot.