A PFM-based Global Convergence Visual Servo Path Planner

As a classical local path planning method, potential field method (PFM) is used widely in the robotics field because of its simplicity and elegance. However, a main drawback of this method is the existence of local minima when generating a path for a robot to follow. In this paper, we present a path planning approach for visual servo by using PFM method to keep the features within the camera field of view (FOV). A rigorous analysis is then presented to prove the global stability of the constructed path planning method. Moreover, the problem of how to obtain a better three-dimensional (3D) camera path is also studied extensively. Simulation results are provided to verify the performance of the proposed path planner.