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Next Generation of Airborne Platforms: From Architecture Design to Sensors Scheduling

Abstract : Airborne platforms such as Remote Piloted Aircraft Systems (RPAS) are operating in highly critical contexts. The next generation of RPAS will be endowed with multifunction sensors (i.e. each sensor offers a large panel of functions to the platform's manager during the mission). As a platform, RPAS carry out a wide collection of complex tasks, thanks to the interleaving of the various services of sensors. The sensors are in charge of collecting data from the environment. In this paper, we aim to design a system as a software medium layer between the platform manager and the hardware resources on board of the airborne platform (i.e. multifunction sensors). Today, the requirements of the platform in terms of autonomy, modularity, robustness and reactivity as well as the industrial constraints call for the design of a new multifunction system architecture. Such a design may rely on multi-agent paradigm since it is modular by design and the agents naturally bring autonomy and pro-activity to the system. This paper presents new and original contributions: (1) an original agentification of the system in the form of a multi-agent architecture that captures the dynamic of the environment by creating tactical objects (i.e. agents) that may appear in the mission theater; (2) agents that generates a plan of tasks according to the resources (e.g. the sensors) he needs; (3) a scheduler that handles the plans of tasks issued by the agents in order to provide an efficient scheduling of sensors.
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Contributor : Ludovic Grivault <>
Submitted on : Wednesday, June 14, 2017 - 2:33:31 PM
Last modification on : Friday, October 16, 2020 - 3:21:15 AM
Long-term archiving on: : Tuesday, December 12, 2017 - 12:57:45 PM


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  • HAL Id : hal-01539119, version 1


Ludovic Grivault, Amal El Fallah-Seghrouchni, Raphaël Girard-Claudon. Next Generation of Airborne Platforms: From Architecture Design to Sensors Scheduling. ICA 2017 - 2nd IEEE International Conference on Agents, Jul 2017, Beijing, China. ⟨hal-01539119v1⟩



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