Multi-Agent Path Finding for Schedule Constrained Automation (Extended Abstract)

Abstract

In modern automation settings, jobs are processed across machines with interdependencies and are subject to limited equipment availability. When transportation between machines is considered, the problem evolves into a complex multi-agent routing task with operational constraints. Existing Multi-Agent Path Finding (MAPF) algorithms address challenges such as robustness and uncertainty, but practical applications involving scheduling constraints often require considerable manual effort for adaptation and heuristic design. In this paper, we introduce MAPF-SC, an extension of MAPF that incorporates scheduling constraints for continuous task flows. We explore the challenges of applying existing techniques to this problem, emphasizing the engineering effort involved in addressing these constraints. Our evaluation investigates the impact of temporal and topological variations on performance, highlighting key factors that influence real-world automation scenarios.