Self-Organization of a Group of Digital Twins of Unmanned Transport Vehicles for Production Tasks in a Smart Workshop
Abstract
The article presents a method for self-organization of a group of digital twins of unmanned transport vehicles (UTVs) in a virtual production space of a smart workshop. The aim is to ensure collision-free collective movement of UTVs during the transportation of workpieces and component parts. This is achieved by adapting the molecular dynamics method, where each vehicle is considered a "quasi-molecule" interacting with other vehicles and environmental elements of the smart workshop through attractive and repulsive potentials. A genetic algorithm is applied to optimize the time required for processing a batch of products, generating quasi-optimal sequences for selecting workpieces and components. Simulations conducted in the Unity environment confirmed the effectiveness of the approach: the deviation from the reference time and energy indicators was less than 5%, and collisions were completely absent during testing.
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