On reduction of oscillations in target tracking by artificial potential field method
Industrial and Information Systems（2014）
摘要
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.
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关键词
gradient methods,least squares approximations,mobile robots,path planning,target tracking,levenberg-marquardt algorithm,artificial potential field method,cluttered environment,gradient descent technique,navigation,oscillation problem,oscillation reduction,second order methods,atificial potential field,mobile robot,optimization,oscillations,trajectory,oscillators,convergence
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