Path planning in static scenarios using image processing and cell decomposition

The path planning is one of the most important areas in robotics. Particularly in static environments, there are different algorithms that provide important solutions to this problem. Most of these algorithms are based on traditional geometric techniques such as: modeling of the free space, Voronoi diagrams and potential fields. This paper proposes an alternative to the strategy of decomposition in cells. The main objective of the algorithm is to identify and evaluate the free cells of the environment, and from them generate a possible path. The performance of the strategy was evaluated using a simulation on different observable static environments.