On reduction of oscillations in target tracking by artificial potential field method

Artificial potential field is a powerful method of navigation for mobile robots in a cluttered environment. Despite the advantages that it offers, this method is not free from local minima and oscillation problems. This paper addresses the oscillation problem near the obstacles and in narrow passages. A comparative study has been made between the traditional gradient descent technique and second order methods and it has been shown that the Levenberg-Marquardt algorithm improves upon the oscillation problem and generates smoother trajectories in fewer steps.