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.
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