TOWARD A GOAL-BASED MISSION PLANNING CAPABILITY - Using PDDL Based Automated Planners

John Bookless, Glenn Callow

2012

Abstract

This paper proposes a generic goal-based mission planning framework which provides an integration environment to support evaluation of existing planning and task assignment technologies. The framework facilitates planning across a team of heterogeneous assets with a distributed capability for generating plans to collaboratively achieve goals. A human operator assigns a team with a top-level goal which the framework then decomposes into a list of tasks that can either be tackled by an individual asset or collectively by a sub-team of assets with the appropriate capabilities. Each asset can generate individual plans with knowledge of the current world state and a goal state. A selection of candidate planners are investigated using the framework including a Hierarchical Task Network (HTN) Planner for goal decomposition and a Partial Ordered PDDL (Planning Domain Definition Language) Planner for action-based plan generation. The developed framework is applied to a search-and-rescue scenario requiring a team of UAVs (Unmanned Aerial Vehicle) to search a specified area of operation.

References

  1. Li, F., Golden, B. L., Wasil, E. A., 2007. The open vehicle routing problem: Algorithms, large-scale test problems, and computational results, Computers & OR, 34(10): 2918-2930.
  2. Long, D., et al, 2000. The AIPS-98 Planning Competition, Artificial Intelligence Magazine, 21(2).
  3. Bellifemine, F., Poggi, A., Rimassa, G., 1999. JADE-A FIPA-compliant agent framework, Proceedings of PAAM, 97-108.
  4. Howden, N. et al, 2001. JACK intelligent agents-summary of an agent infrastructure, 5th International Conference on Autonomous Agents.
  5. d'Iverno, M. et al, 2004. The DMars Architecture: A specification of the distributed multi-agent reasoning system, Autonomous Agents and Multi-Agent Systems, 9: 5-53.
  6. Fox, M., Long, D., 2003. PDDL2.1: An extension to PDDL for expressing temporal planning domains, Journal of Artificial Intelligence Research, 20: 61- 124.
  7. Coles, A. J., Coles, A. I., Fox, M., Long, D., 2010. Forward-Chaining Partial-Order Planning, Proceedings of ICAPS-10.
  8. Hsu, C. W., Wah, B. W., 2008. The SGPlan planning system in IPC-6, Artificial Intelligence.
  9. Brunet, L., Choi, H. L., How, J., 2009. Consensus-based auction approaches for decentralised task assignment, In AIAA Guidance, Navigation and Control Conference and Exhibit.
  10. Osman, I., 1993. Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem, Annals of Operations Research, 41: 421-451.
  11. Coles, A. I., Long, D., Rendell, P., 2010. Experiences with Temporal Planning, Proceedings of the Workshop of the UK Planning and Scheduling Special Interest Group
  12. Fox, M., Long, D., 2002. PDDL+: Modelling continuous time dependent effects, Proceedings of the 3rd International NASA Workshop on Planning and Scheduling for Space.
Download


Paper Citation


in Harvard Style

Bookless J. and Callow G. (2012). TOWARD A GOAL-BASED MISSION PLANNING CAPABILITY - Using PDDL Based Automated Planners . In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-95-9, pages 481-484. DOI: 10.5220/0003718104810484


in Bibtex Style

@conference{icaart12,
author={John Bookless and Glenn Callow},
title={TOWARD A GOAL-BASED MISSION PLANNING CAPABILITY - Using PDDL Based Automated Planners},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2012},
pages={481-484},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003718104810484},
isbn={978-989-8425-95-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - TOWARD A GOAL-BASED MISSION PLANNING CAPABILITY - Using PDDL Based Automated Planners
SN - 978-989-8425-95-9
AU - Bookless J.
AU - Callow G.
PY - 2012
SP - 481
EP - 484
DO - 10.5220/0003718104810484