Solving an Industrial-Scale Warehouse Delivery Problem with Answer Set Programming Modulo Difference Constraints

Abstract

A warehouse delivery problem consists of a set of robots that undertake delivery jobs within a warehouse. Items are moved around the warehouse in response to events. A solution to a warehouse delivery problem is a collision-free schedule of robot movements and actions that ensures that all delivery jobs are completed and each robot is returned to its docking station. While the warehouse delivery problem is related to existing research, such as the study of multi-agent path finding (MAPF), the specific industrial requirements necessitated a novel approach that diverges from these other approaches. For example, our problem description was more suited to formalizing the warehouse in terms of a weighted directed graph rather than the more common grid-based formalization. We formalize and encode the warehouse delivery problem in Answer Set Programming (ASP) extended with difference constraints. We systematically develop and study different encoding variants, with a view to computing good quality solutions in near real-time. In particular, application specific criteria are contrasted against the traditional notion of makespan minimization as a measure of solution quality. The encoding is tested against both crafted and industry data and experiments run using the Hybrid ASP solver clingo[dl].

You Are Not Alone: Towards Cleaning Robot Navigation in Shared Environments through Deep Reinforcement Learning

“…In such a case, there is no hard requirement for information exchange between the robots themselves or specific intelligent interaction modeling. But there is a requirement for a server system that supervises all the tasks [22]. Swarm robotics requires the exchange of information through communication channels between agents in the swarm [23][24][25][26].…”