Cellular automata based real time path planning for mobile robots

Intelligent mobile robotic agents demand optimal motion planners with minimum query time. Most contemporary algorithms lack one of these two required aspects. This paper proposes a cellular automata (CA) based efficient path planning scheme that generates optimal paths in minimum time. A Cellular automata is evolved over the entire environment and subsequently used for shortest path determination. This approach generates a parent-child relationship for each cell in order to minimize the search time. Analysis and simulation results have proven it to be a robust, complete path planning scheme and time efficient both in static and dynamic environments.