Abstract
Autonomous vehicles for in-plant transportation are widely accepted in the industry nowadays. If applied in order picking, efficiency of their operations is essential for the performance of the overall system. Even though the developed systems are tailored to work in highly volatile environments their procedures are programmed in a comparably old-fashioned and inflexible manner. Answer set programming is experiencing a revival due to advances in the development of solving algorithms and computer hardware. This paper is an invited, extended version of Schieweck et al. (Proceedings of the 9th international joint conference on computational intelligence, 2007, [1]), in which several approaches for the application of answer set programming in order picking systems with autonomous vehicles are discussed. In this paper, the provided information on the approachesis extended, the discussion expanded and the paradigm of reactive answer set programming is additionally taken into account.
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