Abstract
The use of Artificial Intelligence (AI) to support the Automated Guided Vehicles (AGV) that are used by industry poses a number of challenges that are specific to smart internal logistics systems that are necessary for agile manufacturing. On the one hand, it might seem that experience with the autonomous navigation system that are used in autonomous vehicles can be easily transferred to AGV. However, in this paper, the authors highlight specific problems that are associated with the navigation system of AGV, which has to reflect its operation in an industrial environment with high level of interaction with other production systems and human staff. On the other hand, it may seem that the wealth of experience from using AI in smart manufacturing can be easily transferred to the use of AGV. However, the authors show that although AGV are production tools, the challenges that are associated with the use of AI can significantly differ from other smart manufacturing areas. The number of challenges that are specific to use of AI for AGV is also discussed. This paper systematizes these challenges and discusses the most promising AI methods that can be used for the internal logistics systems that are based on AGV.
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