This paper describes a dynamical local path-planning algorithm of an autonomous mobile robot available for stationary obstacle avoidance using nonlinear friction. Dynamical path-planning algorithm is considered to accommodate the mobile robot to the dynamic situation of the path-planning nature. Together with the previous virtual force field method, the path of the mobile robot is a solution of a path-planning equation. Local minima problems in stationary environments are solved by introducing nonlinear friction into the chaotic neuron. Because of the nonlinear friction, the proposed path-planner reveals chaotic dynamics in some parameter regions. This new path-planner is feasible to guide, in real-time, the mobile robot to avoid stationary obstacles and to reach the goal. Computer simulations are presented to show the effectiveness of the proposed algorithm.
['Changkyu Choi', 'Sun-Gi Hong', 'Jin-Ho Shin', 'Il-Kwon Jeong', 'Ju-Jang Lee']
Dynamical path-planning algorithm of a mobile robot using chaotic neuron model