Towards ASP-based Scheduling for Industrial Transport Vehicles

Marco De Bortoli, Gerald Steinbauer, Felicitas Fabricius, Maximilian Selmair, Michael Reip, Martin Gebser

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


The increasing number of robots and autonomous vehicles involved in logistics applications leads to new challenges to face for the community of Artificial Intelligence. Web-shop giants, like Amazon or Alibaba for instance, brought this problem to anew level, with huge warehouses and a huge number of orders to deliver with strict deadlines. Coordinating and scheduling such high quantity of tasks over a fleet of autonomous robots is a really complex problem: neither simple imperative greedy algorithms, which compromises over the quality of the solution, nor precise enumeration techniques, which make compromises over the solving time, are any-more feasible to tackle such problems. In this work,we use Answer Set Programming to tackle real-world logistics problems, involving both dynamic task assignment and planning, at the BMW Group and In-cubed IT. Different strategies are tried, and com-pared to the original imperative approach
Original languageEnglish
Title of host publicationJoint Austrian Computer Vision and Robotics Workshop
Number of pages8
Publication statusPublished - Jul 2020


  • ASP
  • Scheduling
  • logistics


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