Document Open Access Logo

Scalable Robotic Intra-Logistics with Answer Set Programming

Author Philipp Obermeier

PDF

File

Thumbnail PDF
PDF
OASIcs.ICLP.2018.24.pdf
  • Filesize: 1.22 MB
  • 5 pages

Document Identifiers

Subject Classification

ACM Subject Classification
  • Computing methodologies → Logic programming and answer set programming
Keywords
  • Answer Set Programming
  • Logistics
  • Planning

Metrics

Abstract

Over time, Answer Set Programming (ASP) has gained traction as a versatile logic programming semantics with performant processing systems, used by a growing number of significant applications in academia and industry. However, this development is threatened by a lack of commonly accepted design patterns and techniques for ASP to address dynamic application on a real-world scale. To this end, we identified robotic intra-logistics as representative scenario, a major domain of interest in the context of the fourth industrial revolution. For this setting, we aim to provide a scalable and efficient ASP-based solutions by (1) stipulating a standardized test and benchmark framework; (2) leveraging existing ASP techniques through new design patterns; and (3) extending ASP with new functionalities. In this paper we will expand on the subject matter as well as detail our current progress and future plans.

Cite As Get BibTex

Philipp Obermeier. Scalable Robotic Intra-Logistics with Answer Set Programming. In Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018). Open Access Series in Informatics (OASIcs), Volume 64, pp. 24:1-24:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/OASIcs.ICLP.2018.24

Author Details

Philipp Obermeier
  • Institute of Computer Science, University of Potsdam, Germany

Funding

This research is partially supported by DFG (550/9).

References

  1. E. Erdem, D. Kisa, U. Öztok, and P. Schüller. A General Formal Framework for Pathfinding Problems with Multiple Agents. In M. desJardins and M. Littman, editors, Proceedings of the Twenty-Seventh National Conference on Artificial Intelligence (AAAI'13), pages 290-296. AAAI Press, 2013. URL: http://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6293.
  2. M. Gebser, P. Obermeier, T. Otto, T. Schaub, O. Sabuncu, V. Nguyen, and T. Son. Experimenting with robotic intra-logistics domains. Theory and Practice of Logic Programming, 2018. To appear. URL: http://arxiv.org/abs/1804.10247.
  3. M. Gebser, P. Obermeier, M. Rasch-Heitmann, and T. Schaub. Routing Driverless Transport Vehicles in Car Assembly with Answer Set Programming. Theory and Practice of Logic Programming, 2018. To appear. URL: http://arxiv.org/abs/1804.10437.
  4. V. Lifschitz. Answer set planning. In D. de Schreye, editor, Proceedings of the International Conference on Logic Programming (ICLP'99), pages 23-37. MIT Press, 1999. Google Scholar
  5. H. Ma and S. Koenig. Optimal Target Assignment and Path Finding for Teams of Agents. In C. Jonker, S. Marsella, J. Thangarajah, and K. Tuyls, editors, Proceedings of the Fifteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS'16), pages 1144-1152. ACM Press, 2016. Google Scholar
  6. H. Ma, J. Li, T. Kumar, and S. Koenig. Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks. In Proceedings of the Sixteenth Conference on Autonomous Agents and MultiAgent Systems (AAMAS'17), pages 837-845. ACM Press, 2017. Google Scholar
  7. V. Nguyen, P. Obermeier, T. Son, T. Schaub, and W. Yeoh. Generalized Target Assignment and Path Finding Using Answer Set Programming. In C. Sierra, editor, Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI'17), pages 1216-1223. IJCAI/AAAI Press, 2017. Google Scholar
  8. P. Surynek. An Optimization Variant of Multi-Robot Path Planning Is Intractable. In M. Fox and D. Poole, editors, Proceedings of the Twenty-fourth National Conference on Artificial Intelligence (AAAI'10), pages 1261-1263. AAAI Press, 2010. URL: http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/view/1768.
  9. J. Yu and S. LaValle. Multi-agent Path Planning and Network Flow. In E. Frazzoli, T. Lozano-Pérez, N. Roy, and D. Rus, editors, Proceedings of the Tenth Workshop on the Algorithmic Foundations of Robotics (WAFR'12), volume 86 of Springer Tracts in Advanced Robotics, pages 157-173. Springer-Verlag, 2012. URL: http://dx.doi.org/10.1007/978-3-642-36279-8_10.
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact