Architecture for the Automatic Generation of Plans for Multiple UAS from a Generic Mission Description
A planning approach for a platform composed of multiple unmanned aerial systems is presented in this paper. The research activities are focused on the interoperability, task allocation and task planning problems within the system. In order to tackle with the interoperability problem between the vehicles of the platform and other external systems, C-BML has been chosen as the standard language to formalize the description of the missions. Regarding the planning problems involved, several planners have been applied to solve them: a task allocation planner to create an initial assignment of tasks to vehicles, a symbolic planner for high-level reasoning and tools for geometric reasoning. The main contribution of the paper is the use of consolidated task planning techniques to automatically generate low-level plans from a mission described in C-BML, filling the gap between interoperability and automatic plan generation for missions where multiple heterogeneous aerial platforms are involved. The approach has been tested in missions involving multiple surveillance and 3D map generation tasks and the paper includes experimental results.
KeywordsSymbolic planning Task planning Task allocation Multiple UAS Interoperability
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- 4.Currie, K., Tate, A., Bridge, S.: O-Plan: the open planning architecture (1990)Google Scholar
- 5.Gerevini, A., Kuter, U., Nau, D., Saetti, A., Waisbrot, N.: Combining domain-independent planning and HTN planning: the duet planner (2008)Google Scholar
- 7.Helmert, M.: The fast downward planning system. J. Artif. Intell. Res., 191–246 (2006)Google Scholar
- 10.Lagriffoul, F., Dimitrov, D., Bidot, J., Saffiotti, A., Karlsson, L.: Efficiently combining task and motion planning using geometric constraints. Int. J. Robot. Res. 33(14), 1726–1747 (2014). doi: 10.1177/0278364914545811. http://ijr.sagepub.com/content/33/14/1726.abstract CrossRefGoogle Scholar
- 11.LaValle, S.M.: Planning algorithms. Available at http://planning.cs.uiuc.edu/ (2006)
- 13.Maza, I., Ollero, A.: Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms Distributed Autonomous Robotic Systems, vol. 6, pp 221–230. Springer, Berlin Heidelberg New York (2007). http://www.springerlink.com/content/978-4-431-35869-5#section=288931&page=1&locus=0
- 16.Red Hat open source community: OptaPlanner. http://www.optaplanner.org/ (2014). Accessed 12 December 2014
- 17.Rohmer, E., Singh, S., Freese, M.: V-rep: a versatile and scalable robot simulation framework. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 1321–1326 (2013). doi: 10.1109/IROS.2013.6696520
- 18.Shivashankar, V., Alford, R., Kuter, U., Nau, D.: The GoDeL Planning System: A More Perfect Union of Domain-independent and Hierarchical Planning Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, pp 2380–2386 (2013). http://dl.acm.org/citation.cfm?id=2540128.2540470
- 19.SISO: Standard for: Coalition battle management language (C-BML) phase 1 (2012)Google Scholar
- 20.Wilkins, D.E.: Practical planning: extending the classical AI planning paradigm. Morgan Kaufmann, San Francisco (1988)Google Scholar
- 21.Wolfe, J., Marthi, B., Russell, S.J.: Combined task and motion planning for mobile manipulation. Tech. Rep. UCB/EECS-2010-27, EECS Department, University of California, Berkeley. http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-27.html (2010)