For global optimal path planning of mobile robot, a path planning algorithm based on cellular automata is
proposed. This algorithm defines the robot’s starting point, target point and the obstacle points in the environment as a
group of discrete cellular states, and builds cellullar automata model of environment, then designs evolution rules by the
robot’s Manhattan distance. Finally, the optimal path can be found out according to the cellular states after evolution. The
simulation results show the effectiveness of the proposed algorithm.