Towards Long-Term Autonomy Based on Temporal Planning

  • Yaniel CarrenoEmail author
  • Ronald P. A. Petrick
  • Yvan Petillot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11650)


This paper investigates the application of temporal planning to multiple robots in long-term missions, using the OPTIC and POPF temporal planners. We design a new planning domain, motivated by a realistic indoor-outdoor scenario. In particular, we investigate plan concurrency, makespan and plan generation time in the multi-robot problem and propose a schema which has been shown to improve plan quality while significantly reducing planning time for the multi-agent problem. Experiments are done in simulation using ROS and Gazebo, and demonstrated in missions with concurrent actions. The ROSPlan framework is also extended to work with multiple robots and used to integrate the planners in ROS. OPTIC provides the best overall solution considering the domain complexity and mission execution in the environment.


Temporal-planning Multi-agent Long-term autonomy 


  1. 1.
    Benton, J., Coles, A.J., Coles, A.: Temporal planning with preferences and time-dependent continuous costs. In: International Conference on Automated Planning and Scheduling (2012)Google Scholar
  2. 2.
    Cashmore, M., Coles, A., Cserna, B., Karpas, E., Magazzeni, D., Ruml, W.: Situated planning for execution under temporal constraints. In: Learning, and Execution for Goal Directed Autonomy, AAAI Spring Symposium on Integrating Representation, Reasoning (2018)Google Scholar
  3. 3.
    Cashmore, M., et al.: ROSPlan: planning in the robot operating system. In: International Conference on Automated Planning and Scheduling, pp. 333–341 (2015)Google Scholar
  4. 4.
    Chanel, C.P.C., Lesire, C., Teichteil-Königsbuch, F.: A robotic execution framework for online probabilistic (re)planning. In: Proceedings of ICAPS (2014)Google Scholar
  5. 5.
    Chrpa, L., Pinto, J., Ribeiro, M.A., Py, F., Sousa, J., Rajan, K.: On mixed-initiative planning and control for autonomous underwater vehicles. In: IROS, pp. 1685–1690 (2015)Google Scholar
  6. 6.
    Coles, A.J., Coles, A., Fox, M., Long, D.: Forward-chaining partial-order planning. In: ICAPS, pp. 42–49 (2010)Google Scholar
  7. 7.
    Crosby, M., Petrick, R: Temporal multiagent planning with concurrent action constraints. In: ICAPS Workshop on Distributed and Multi-Agent Planning (DMAP) (2014)Google Scholar
  8. 8.
    De Weerdt, M., Ter Mors, A., Witteveen, C.: Multi-agent planning: an introduction to planning and coordination. In: Handouts of the European Agent Summer. Citeseer (2005)Google Scholar
  9. 9.
    Della Penna, G., Magazzeni, D., Mercorio, F.: A universal planning system for hybrid domains. Appl. Intell. 36(4), 932–959 (2012)CrossRefGoogle Scholar
  10. 10.
    Eyerich, P., Mattmüller, R., Röger, G.: Using the context-enhanced additive heuristic for temporal and numeric planning. In: Towards Service Robots for Everyday Environments, pp. 49–64 (2012)Google Scholar
  11. 11.
    Fernandez-Gonzalez, E., Williams, B., Karpas, E.: ScottyActivity: mixed discrete-continuous planning with convex optimization. JAIR 62, 579–664 (2018)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Fox, M., Long, D.: PDDL2.1: an extension to PDDL for expressing temporal planning domains. JAIR 20, 61–124 (2003)CrossRefGoogle Scholar
  13. 13.
    Ingham, M., Ragno, R., Williams, B.C.: A reactive model-based programming language for robotic space explorers. In: Proceedings of ISAIRAS-01 (2001)Google Scholar
  14. 14.
    Marques, T., Pinto, J., Dias, P., de Sousa, J.T.: MvPlanning: a framework for planning and coordination of multiple autonomous vehicles. In: OCEANS-Anchorage, pp. 1–6 (2017)Google Scholar
  15. 15.
    McDermott, D., et al.: PDDL - the planning domain definition language (version 1.2). Technical report CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control (1998)Google Scholar
  16. 16.
    McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., McEwen, R.: A deliberative architecture for AUV control. In: IEEE International Conference on Robotics and Automation, pp. 1049–1054 (2008)Google Scholar
  17. 17.
    Muscettola, N., Dorais, G.A., Fry, C., Levinson, R., Plaunt, C.: IDEA: planning at the core of autonomous reactive agents. In: NASA Workshop on Planning and Scheduling for Space (2002)Google Scholar
  18. 18.
    Nunes, E., Gini, M.L.: Multi-robot auctions for allocation of tasks with temporal constraints. In: AAAI, pp. 2110–2116 (2015)Google Scholar
  19. 19.
    Nunes, E., McIntire, M., Gini, M.: Decentralized multi-robot allocation of tasks with temporal and precedence constraints. Adv. Robot. 31(22), 1193–1207 (2017)CrossRefGoogle Scholar
  20. 20.
    Piotrowski, W., Fox, M., Long, D., Magazzeni, D., Mercorio, F.: Heuristic planning for hybrid systems. In: AAAI, pp. 4254–4255 (2016)Google Scholar
  21. 21.
    Ponda, S., Redding, J., Choi, H.-L., How, J.P., Vavrina, M., Vian, J.: Decentralized planning for complex missions with dynamic communication constraints. In: American Control Conference, pp. 3998–4003 (2010)Google Scholar
  22. 22.
    Quigley, M., et al.: ROS: an open-source Robot Operating System. In: ICRA Workshop on Open Source Software (2009)Google Scholar
  23. 23.
    Schillinger, P., Bürger, M., Dimarogonas, D.V.: Simultaneous task allocation and planning for temporal logic goals in heterogeneous multi-robot systems. Int. J. Robot. Res. 37, 818–838 (2017)CrossRefGoogle Scholar
  24. 24.
    Tran, T.T., Vaquero, T., Nejat, G., Beck, J.C.: Robots in retirement homes: applying off-the-shelf planning and scheduling to a team of assistive robots. JAIR 58, 523–590 (2017)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Veloso, M.M., Biswas, J., Coltin, B., Rosenthal, S.: CoBots: robust symbiotic autonomous mobile service robots. In: IJCAI, p. 4423 (2015)Google Scholar
  26. 26.
    Zhang, Z., Wang, J., Xu, D., Meng, Y.: Task allocation of multi-AUVs based on innovative auction algorithm. In: Proceedings of ISCID, vol. 2, pp. 83–88. IEEE (2017)Google Scholar
  27. 27.
    Hawes, N., et al.: The strands project: long-term autonomy in everyday environments. IEEE Robot. Autom. Mag. 24(3), 146–156 (2017)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yaniel Carreno
    • 1
    Email author
  • Ronald P. A. Petrick
    • 1
  • Yvan Petillot
    • 1
  1. 1.Edinburgh Centre for RoboticsHeriot-Watt UniversityEdinburghUK

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