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Planning optimal routes for Autonomuos Guided Vehicle transport systems is a crucial task for improving productivity and efficiency in several industrial applications. For such systems, there already exist models based on optimization approaches, which can
compute an optimal solution, but become infeasible as the number of agents increases. In my work, a different approach for such routing environments is presented, followed by
the analysis and implementation of an algorithm capable to provide suboptimal solutions for route planning problems in real time. The key concept in the investigated algorithm is avoiding problems at the time of route planning, by creating a set of routes that are conflict-, collision- and deadlock-free by design. The model, on which this work is based, was modified to support multiple type of agents - including ground and aerial vehicles - in the same environment, by the introduction of movement primitives and a three-dimensional planning graph. The algorithm was extended to handle practical problems emerging from unrealistic preconditions, and several experiments were carried out to validate my result. The experiments took place in the simulation system, created as a part of this research.
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