On the Synthesis of Guaranteed-Quality Plans for Robot Fleets in Logistics Scenarios via Optimization Modulo Theories
This addresses scheduling challenges for robot fleets in logistics, offering a guaranteed optimal approach, though it appears incremental as it builds on OMT methods.
The paper tackles the problem of multi-robot scheduling in manufacturing by using Optimization Modulo Theories (OMT) to guarantee optimal solutions, whereas existing methods are heuristic.
In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management. In this paper we report on the usage of Optimization Modulo Theories (OMT) to solve certain multi-robot scheduling problems in this area. Whereas currently existing methods are heuristic, our approach guarantees optimality for the computed solution. We do not only present our final method but also its chronological development, and draw some general observations for the development of OMT-based approaches.