Research demonstrates efficient path planning for autonomous mobile robots in warehouses, suggesting reduced operating costs.
Up to 60 percentages of realized costs in warehouses can be attributed to the collection of ordered products. As the use of robots expands, the research aims to reduce operating costs and make robots more efficient in warehouses. In this regard, it is necessary to optimize the robot's path in the warehouse. The emphasis is on Autonomous Mobile agents, a type of intelligent vehicle that can perceive its environment. Autonomous Mobile Robot path planning is formulated as a Travelling Salesman Problem. In the paper, the goal of Travelling Salesman Problem is to minimize travel distance. Due to the problem’s complexity, the robot’s path was planned using a Genetic Algorithm. The optimal path is determined in the warehouse where certain products need to be loaded and delivered for further transport.
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Nikolić et al. (2025) studied this question.
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