K. Ioannidis, G.Ch. Sirakoulis, and I. Andreadis (Greece)
Cooperative robots, path planning, cellular automata and ant colony optimization
The path planning problem is one of the major tasks in the field of robotics. In systems of multiple robots, the creation of collision free paths becomes even more complex due to the fact that all robots must complete one specific task as a team. Forming a specific pattern while the robotic team covers a predefined distance, is a common task in cooperative robotics. The complexity of the problem increases with the number of members of the team. This paper proposes a novel path planning algorithm using a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques to create collision free paths for each robot of the team. The team is divided into subgroups and optimal paths are created using an ACO algorithm. If the algorithm is not applicable, for example, due to lack of pheromone, then paths are created using a CA path planner. The simplicity of the method relies on the fact that it uses fixed discrete values and a probabilistic method to reduce the complexity of the entire system. Simulation results indicate that the proposed method can produce accurate collision free paths even in systems comprising of large number of robots.
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