Dynamical path-planning algorithm of a mobile robot using chaotic neuron model

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.

Authors

• Changkyu Choi
• Sun-Gi Hong
• Jin-Ho Shin
• Il-Kwon Jeong
• Ju-Jang Lee

Keywords

• Path planning
• Heuristic algorithms
• Mobile robots
• Chaos
• Friction
• Nonlinear equations
• Neurons
• Computer simulation
• Dynamical
• Pathfinding
• Mobile Robot
• Local Minima
• Solution Of Equation
• Local Problems
• Parameter Region
• Chaotic Dynamics
• Automated Guided Vehicles
• Static Obstacles
• Virtual Force
• Local Minimum Problem
• External Force
• Equilibrium Point
• Repulsive Forces
• Attractive Forces
• Solutions Of Differential Equations
• Newton’s Second Law
• Robot Dynamics
• Negative Infinity
• Velocity Of The Robot
• Sensor Suite