Abstract
Due to increased demands related to flexible product configurations, frequent order changes, and tight delivery windows, there is a need for flexible production using AI methods. A way of addressing this is the use of temporal planning as it provides the ability to generate plans for complex goals while considering temporal aspects such as deadlines, concurrency, and durations. Drawbacks in applying such methods in dynamic environments are their high and unpredictable planning time as well as the limited ability to react to unexpected delays during the plan execution. In this paper, we address these issues with a temporal planning and execution framework that employs an online goal management strategy to deal with high and variable computational costs, and a plan dispatcher that takes the future temporal feasibility of plans into consideration. The framework has been evaluated using the RoboCup Logistics League simulation framework.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Benton, J., Coles, A., Coles, A.: Temporal planning with preferences and time-dependent continuous costs. In: Proceedings of the International Conference on Automated Planning and Scheduling, vol. 22, no. 1, pp. 2–10, May 2012. https://ojs.aaai.org/index.php/ICAPS/article/view/13509
Bit-Monnot, A.: Temporal and Hierarchical Models for Planning and Acting in Robotics. Ph.D. thesis, Université de Toulouse (2016)
Cashmore, M., et al.: Rosplan: planning in the robot operating system. In: Proceedings International Conference on Automated Planning and Scheduling, ICAPS 2015, pp. 333–341, January 2015
Castillo, L., Fdez-Olivares, J., González-Muñoz, A.: A temporal constraint network based temporal planner, January 2002
Cimatti, A., Do, M., Micheli, A., Roveri, M., Smith, D.E.: Strong temporal planning with uncontrollable durations. Artif. Intell. 256, 1–34 (2018)
Dechter, R., Meiri, I., Pearl, J.: Temporal constraint networks. Artif. Intell. 49(1), 61–95 (1991). https://doi.org/10.1016/0004-3702(91)90006-6, https://www.sciencedirect.com/science/article/pii/0004370291900066
Egger, V., Fürbaz, L., Haas, S., Krickl, S., Ludwiger, J., Martin, I., et al.: Robocup logistics league Graz robust and intelligent production system grips (2018)
Erol, K., Hendler, J., Nau, D.S.: HTN planning: complexity and expressivity. In: AAAI, vol. 94, pp. 1123–1128 (1994)
Fox, M., Long, D.: PDDL2.1: an extension to PDDL for expressing temporal planning domains. J. Artif. Intell. Res. (JAIR) 20, 61–124 (12 2003)
Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Clingo= asp+ control. arXiv preprint arXiv:1405.3694 (2014)
Ingrand, F., Chatila, R., Alami, R., Robert, F.: PRS: a high level supervision and control language for autonomous mobile robots. In: Proceedings of IEEE International Conference on Robotics and Automation, vol. 1, pp. 43–49 (1996)
Ingrand, F., Ghallab, M.: Deliberation for autonomous robots: a survey. Artif. Intell. 247, 10–44 (2017). https://www.sciencedirect.com/science/article/pii/S0004370214001350, special Issue on AI and Robotics
Morris, P.: Dynamic controllability and dispatchability relationships. In: Simonis, H. (eds.) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2014. LNCS, vol. 8451, pp. 464–479. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07046-9_33
Morris, P., Muscettola, N., Vidal, T.: Dynamic control of plans with temporal uncertainty. In: Proceedings of the 17th International Joint Conference on A.I. (IJCAI-01), August 2003
Muscettola, N., Morris, P., Tsamardinos, I.: Reformulating temporal plans for efficient execution. In: Principles of Knowledge Representation and Reasoning (1998)
Nau, D., Ghallab, M., Traverso, P.: Automated Planning: Theory & Practice. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2004)
Niemueller, T., Ewert, D., Reuter, S., Ferrein, A., Jeschke, S., Lakemeyer, G.: RoboCup Logistics League Sponsored by Festo: A Competitive Factory Automation Testbed, pp. 605–618, October 2016
Niemueller, T., Hofmann, T., Lakemeyer, G.: Goal reasoning in the clips executive for integrated planning and execution. In: Proceedings of the International Conference on Automated Planning and Scheduling, vol. 29, no. 1, pp. 754–763, May 2021. https://ojs.aaai.org/index.php/ICAPS/article/view/3544
Niemueller, T., Karpas, E., Vaquero, T., Timmons, E.: Planning competition for logistics robots in simulation. In: International Conference on Automated Planning and Scheduling (ICAPS) - Workshop on Planning and Robotics (PlanRob) (2016)
Van Den Briel, M., Sanchez, R., Do, M., Kambhampati, S.: Effective approaches for partial satisfaction (over-subscription) planning. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 562–569 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
De Bortoli, M., Steinbauer-Wagner, G. (2024). Temporal Planning and Acting in Dynamic Domains. In: Buche, C., Rossi, A., Simões, M., Visser, U. (eds) RoboCup 2023: Robot World Cup XXVI. RoboCup 2023. Lecture Notes in Computer Science(), vol 14140. Springer, Cham. https://doi.org/10.1007/978-3-031-55015-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-031-55015-7_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-55014-0
Online ISBN: 978-3-031-55015-7
eBook Packages: Computer ScienceComputer Science (R0)