Unmanned Aerial Vehicle Coverage Path Planning Algorithm Based on Cellular Automata*

Real-time unmanned aerial vehicle coverage path planning is a challenging task. Although different patterns are outlined and optimized, the algorithm of patterns generation given the width of the sensor’s footprint and the map with obstacles is rarely studied. A Cellular Automaton (CA) based algorithm is proposed and implemented for the spiral pattern and tested in maps with obstacles on the corner and off the edge. The CA is asynchronously updated and there is only one UAV- cell, whose time series indexes through the computing can be assigned as the coverage path. The coverage path planning algorithm proposed in the paper is fast because of the intrinsic discreteness of CA.