Abstract
In this chapter, a unified architecture is proposed for a robot team in order to accomplish several tasks based on the application of an enhanced Cellular Automata (CA) path planner. The presented path planner can produce adequate collision-free pathways with minimum hardware resources and low complexity levels. During the course of a robot team to its final destination, dynamic obstacles are detected and avoided in real time as well as coordinated movements are executed by applying cooperations in order to maintain the team’s initial formation. The inherit parallelism and simplicity of CA result in a path planner that requires low computational resources and thus, its implementation in miniature robots is straightforward. Cooperations are limited to a minimum so that further resource reduction can be achieved. For this purpose, the basic fundamentals of another artificial intelligence method, namely Ant Colonies Optimization (ACO) technique, were applied. The entire robot team is divided into equally numbered subgroups and an ACO algorithm is applied to reduce the complexity. As each robot moves towards to its final position, it creates a trail of an evaporated substance, called “pheromone”. The “pheromone” and its quantity are detected by the following robots and thus, every robot is absolved by the necessity of continuous communication with its neighbors. The total complexity of the presented architecture results to a possible implementation using a team of miniature robots where all available resources are exploited.
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Ioannidis, K., Sirakoulis, G.C., Andreadis, I. (2015). Cellular Robotic Ants Synergy Coordination for Path Planning. In: Sirakoulis, G., Adamatzky, A. (eds) Robots and Lattice Automata. Emergence, Complexity and Computation, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-10924-4_9
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