A sub goal seeking approach for reactive navigation in complex unknown environments
Robotics and Autonomous Systems
Virtual sphere algorithms for orthodrome-based collision-free & smooth robot motion
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
New Potential Functions with Random Force Algorithms Using Potential Field Method
Journal of Intelligent and Robotic Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
Behaviour generation in humanoids by learning potential-based policies from constrained motion
Applied Bionics and Biomechanics
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This paper investigates the inherent oscillation problem of potential field methods (PFMs) in the presence of obstacles and in narrow passages. These problems can cause slow progress and system instability in implementation. To overcome these two problems, in this paper, we propose a modification of Newton's method. The use of the modified Newton's method, which applies anywhere C2 continuous navigation functions are defined, greatly improves system performance when compared to the standard gradient descent approach. To the best of our knowledge, ours is the first systematic approach to the oscillation problems in PFMs. We have validated this technique by comparing its performance with the gradient descent method in obstacle-avoidance tasks with different potential models and parameter changes.