Abstract
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 language | English |
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Title of host publication | Joint Austrian Computer Vision and Robotics Workshop |
Pages | 34-41 |
Number of pages | 8 |
Publication status | Published - Jul 2020 |
Keywords
- ASP
- Scheduling
- logistics