The Experts below are selected from a list of 299316 Experts worldwide ranked by ideXlab platform
Rainer Koelle - One of the best experts on this subject based on the ideXlab platform.
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Towards developing a security Situation Management information exchange model
2017 Integrated Communications Navigation and Surveillance Conference (ICNS), 2017Co-Authors: Rainer KoelleAbstract:• NextGen and SESAR offer an unique (“technological”) opportunity • The approach to security and a security capability is not addressed due to political and operational priorities • GAMMA addresses this void offering “dual use” / complementary solutions to SESAR • GAMMA developed a Security Situation Management Concept of Operations that allows for • a modular / iterative implementation and build up of a “security function” in ATM/Air Navigation • distributed Situation Management and decision-making recognising “classical” ATM actors and security actors (i.e. GAMMA organisation) • Hierarchical national implementation and wider regional collaboration • SWIM offers the platform and allows for iterative embedding of the GAMMA Security Solution & Information Model • Definition of Security Information Exchange Model
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Towards validating a security Situation Management capability
2016 Integrated Communications Navigation and Surveillance (ICNS), 2016Co-Authors: Tim H. Stelkens-kobsch, Rainer Koelle, Denis Kolev, Michael Finke, Raoul LahaijeAbstract:With SESAR and NextGen readying towards implementing novel operational concepts and technical enablers in ATM/CNS, the question of how to manage security in a dynamic environment across a highly distributed and networked system gains higher attention. The Global ATM Security Management project (GAMMA) addresses the development of such a security Situation Management capability. Following the September 11 attacks and major large-scale outages of critical infrastructures, the security of air navigation has emerged as a critical capability gap. On-going transformation programs like SESAR and NextGen are moving into the deployment phase with limited to none tangible security solutions. GAMMA addresses this gap by investigating a security Situation Management capability. The framework of this capability is devised as a distributed network of aviation stakeholders that jointly collaborate in identifying and localizing security incidents while considering the constraints given by the different participants, national responsibilities, and collaboration-related requirements. This paper addresses the preparatory work for the validation of an initial security Situation Management capability. For that purpose, project partners setup a joint configuration and trial network for the security functions and systems developed in the frame of a real-time human-in-the-loop simulation. The simulation results have been measured against the mapping of the operational concept and validation requirements, in particular in terms of Situational awareness on the operator side and networked incident Management response. These results will inform the further validation activities of the project.
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Security Situation Management - developing a concept of operations and threat prediction capability
2015 IEEE AIAA 34th Digital Avionics Systems Conference (DASC), 2015Co-Authors: Denis Kolev, Rosa Ana Casar Rodriguez, Rainer Koelle, Patrizia MontefuscoAbstract:This paper addresses a collaborative security Situation Management capability for air navigation. In particular, we formulate the development of a threat prediction capability as a Situation Management problem mapping the concepts of Situation awareness and information fusion. Air transportation and air navigation is undergoing a fundamental transformation. This also requires novel approaches to system security and the Management of security incidents across a network of actors. The Global ATM Security Management project addresses this problem space. The work reported in this paper, conceptualizes a security function that supports the Management of security incidents on a local, national, and regional level supporting the collaborative effort of classical air traffic Management stakeholders and security stakeholders. The security function is based on a network of distributed nodes and capabilities. One such a capability is the threat prediction model. This component is based on a representation of the (sub-) system context as a network of supporting assets, event detection sensors, and associated security controls. Based on the description of the (sub-)system context as a sequence of Situations, the threat prediction capability addresses the identification of a security incident and its potential impact as an optimization problem. This paper reflects the work of the first year of the project. In particular, it demonstrates the general feasibility of the approach and the further modelling and preparatory work for further validation activities.
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ARES - Security Situation Management: Towards Developing a Time-Critical Decision Making Capability for SESAR
2014 Ninth International Conference on Availability Reliability and Security, 2014Co-Authors: Rainer KoelleAbstract:This paper addresses dynamic security Management in air navigation as a distributed collaborative agent problem and identifies a modelling approach for the implementation of a Situation Management capability in ATM. The traditional focus of aviation security is on preventive security aircraft and airport measures. When it comes to air navigation, the concept and scope of security is evolving. This goes in hand with the understanding and the implementation of security requirements and capabilities in new system developments. Security incident Management is a research gap in the on-going transformation programmes SESAR and NextGen. This paper proposes an engineering concept for the development of a dynamic security incident Management capability for the future ATM system context (e.g. SESAR) based on the findings of previous research and the associated development of a Situation Management framework model. The results obtained demonstrate the general applicability of the Situation Management modelling approach to the design and validation of such a dynamic security Management capability as part of the recently launched EU project on Global ATM Security Management (GAMMA). A set of principal research requirements for this project is derived addressing the emerging need for security incident Management capabilities in general, e.g. self-protection / resilience, emergency response. The proposed modelling approach and the anticipated GAMMA deliverables offer an opportunity to address the research gap of SESAR and provide novel technological solutions to the envisaged European Security Operation Centre recently proposed under the umbrella of the centralised services for European ATM.
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Towards a distributed Situation Management capability for SESAR and NextGen
2012 Integrated Communications Navigation and Surveillance Conference, 2012Co-Authors: Rainer Koelle, Alex TarterAbstract:This paper is concerned with the design of a distributed aviation security Situation Management capability in SESAR and NextGen. This research-in-progress report presents an approach to distributed Situation Management based on the concepts of network-centric operations and agent-based modeling. In particular, One of the key issues in aviation security is that despite their catastrophic magnitude, incidents are rare and their precursors hard to identify. The anticipated growth of aviation will increase this challenge as the amount of air traffic will double by 2025, and the future ATM System will see a higher integration of manned and unmanned air vehicles with significantly different capabilities to interact with on-board Situations. We envision a highly integrated air transportation system and the capability to process relevant Situational information elements. The described Situation Management problem is modeled as a multi-agent information problem. Situation Management is viewed as an emergent property of collaborative systems including both human operators and technological agents. This paper addresses the challenges and conceptual modelling of an agentbased simulation of the future aviation and air traffic Management environment. The results obtained indicate that automated support for Situation Management in aviation security is feasible and capable of supporting distributed information sharing and early identification of incidents. Also of importance is that this capability will not place additional constraints on the future ATM System as it can be designed as a data service of the envisaged system-wide information Management infrastructure.
James Llinas - One of the best experts on this subject based on the ideXlab platform.
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FUSION - Situation Management in counter-insurgency operations: An overview of operational art and relevant technologies
2011Co-Authors: James LlinasAbstract:Understanding the concept of employment (COE) for Information Fusion or other analysis/decision-aiding technology is key to the evaluation of its effectiveness; this paper studies and characterizes the COE for Counterinsurgency applications as drawn from open literature and some interchanges with U.S. Army staff. Managing and executing Counterinsurgency (COIN) Situations is complicated business. Collectively, the broad elements of the decision-action space can be broken into “direct” and “indirect” classes of actions, where direct actions are those focused on insurgent force structure in the traditional military sense, and indirect actions those focused on undermining support to the insurgents while simultaneously attacking them militarily. Invoking military doctrine dating from the ideas of a French general in the 1800's, the US Army has developed a response framework involving various “Lines of Effort” and the notions of Effects-Based Operations to achieve behavioral changes in insurgents as Desired Effects as regards the indirect operations. By and large the Situation Management framework requires consideration of notions of Complex Adaptive Systems; the paper will make remarks about this SIMA-CAS context. Intelligence support to this Operational Doctrine requires capabilities in Hard and Soft Fusion technology, methods of Influence Networks, Petri Nets, Sequential Decision Making under Extreme Uncertainty, and Model Predictive Control, among other technologies. This paper will provide an overview of the concepts of the operational doctrine itself and the employment of these technologies in this modern-day military operational doctrine for the Counterinsurgency domain.
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reflections on concepts of employment for modern information fusion and artificial intelligence technologies Situation Management decision making under varying uncertainty and ambiguity sequential decision making learning prediction and trust
Hybrid Artificial Intelligence Systems, 2011Co-Authors: James LlinasAbstract:Information Fusion (IF) is fundamentally an estimation process that attempts to automatically form a best approximated state of an unknown true world Situation, typically from both observational and contextual data. To the degree possible, this process and its algorithms and methods also employ any deductive knowledge that model the evolutionary dynamics of the focal elements of interest in this world. Artificial Intelligence (AI) technologies are often directed to similar goals, and employ similar informational and knowledge components. For many modern problems of interest, there are factors that result in observational data whose quality is unknown, and for which the a priori deductive knowledge models are non-existent or weak. Moreover, even for conventional IF applications where uncertainties of interest are known or estimable, the Concepts of Employment that involve sequential estimation and decisionmaking dynamics have not been very well studied and integrated into the frameworks of understanding for the use of such IF capability. This talk will review a number of interrelated topics that bear on the thinking of how IF technologies will be used in these stressful and critical environments. It will review a previously-proposed overarching Situation Management process model, the modern (and controversial) literature on decision-making under severe uncertainty, aspects and implications of sequential operations on decision-making, as well as Learning and Prediction dynamics as they bear on IF applications. Some remarks will also be included on the dynamics of human trust in automated systems, a topic under current study at the Center for Multisource Information Fusion at Buffalo.
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HAIS (1) - Reflections on concepts of employment for modern information fusion and artificial intelligence technologies: Situation Management, decision making under varying uncertainty and ambiguity, sequential decision-making, learning, prediction,
Lecture Notes in Computer Science, 2011Co-Authors: James LlinasAbstract:Information Fusion (IF) is fundamentally an estimation process that attempts to automatically form a best approximated state of an unknown true world Situation, typically from both observational and contextual data. To the degree possible, this process and its algorithms and methods also employ any deductive knowledge that model the evolutionary dynamics of the focal elements of interest in this world. Artificial Intelligence (AI) technologies are often directed to similar goals, and employ similar informational and knowledge components. For many modern problems of interest, there are factors that result in observational data whose quality is unknown, and for which the a priori deductive knowledge models are non-existent or weak. Moreover, even for conventional IF applications where uncertainties of interest are known or estimable, the Concepts of Employment that involve sequential estimation and decisionmaking dynamics have not been very well studied and integrated into the frameworks of understanding for the use of such IF capability. This talk will review a number of interrelated topics that bear on the thinking of how IF technologies will be used in these stressful and critical environments. It will review a previously-proposed overarching Situation Management process model, the modern (and controversial) literature on decision-making under severe uncertainty, aspects and implications of sequential operations on decision-making, as well as Learning and Prediction dynamics as they bear on IF applications. Some remarks will also be included on the dynamics of human trust in automated systems, a topic under current study at the Center for Multisource Information Fusion at Buffalo.
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Quantitative aspects of Situation Management: measuring and testing Situation Management concepts
Intelligent Sensing Situation Management Impact Assessment and Cyber-Sensing, 2009Co-Authors: James LlinasAbstract:The Data and Information Fusion domains have for some time addressed the issues involved with Situation Estimation and Situation Refinement as part of the characterization of the "higher" levels of fusion processing, meaning those levels of processing that deal with more abstract and complex world states of interest that people call "Situations". It is usually agreed however that at the moment at least the research in the Data and Information Fusion (DIF) field has by far been on the aspects of estimating single and sometimes multiple-object attributes from composite observational data, and usually from electronic or physics-based sensing devices such as radars and imaging systems, that is, on the so-called "lower" levels of fusion. As both the world and the technology have changed, and as research in the DIF arena has matured, there has been a considerable interest in directing the research to methods for estimating the higher state levels of DIF, usually called Situation Refinement and Threat or Impact Refinement, and related to "Level 2" and "Level 3" of the well-known "JDL" DIF process Model (Ref 1). Note that the "refinement" term is important, implying an awareness of the fact that the focus of DIF processing is almost always on dynamic events in the world; it also reflects the need for a temporally-adaptive, recursive state estimation process.
Lundy Lewis - One of the best experts on this subject based on the ideXlab platform.
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Peer-to-peer coupled agent systems for distributed Situation Management
Information Fusion, 2010Co-Authors: John F Buford, Gabriel Jakobson, Lundy LewisAbstract:Large scale Situation Management applications such as disaster recovery and network-centric battle Management are characterized by distributed heterogeneous agent platforms with dynamic agent populations, highly variable network connectivity and bandwidth, and localized Situation knowledge and event collection. We describe a new agent model and an integrated peer-to-peer architecture which addresses these requirements. We present an extension of the BDI agent model which allows it to be used in highly reactive applications. We describe the use of multi-hop peer-to-peer overlays which provides highly scalable coupling of distributed agent platforms. Finally, we describe a two-phase semantic discovery mechanism which serves as a basis for agents to share events and Situations across the overlay.
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Using gaming engines and editors to construct simulations of fusion algorithms for Situation Management
Cyber Security Situation Management and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 2010Co-Authors: Lundy Lewis, Nolan Distasio, Christopher WrightAbstract:In this paper we discuss issues in testing various cognitive fusion algorithms for Situation Management. We provide a proof-of-principle discussion and demo showing how gaming technologies and platforms could be used to devise and test various fusion algorithms, including input, processing, and output, and we look at how the proof-of-principle could lead to more advanced test beds and methods for high-level fusion in support of Situation Management. We develop four simple fusion scenarios and one more complex scenario in which a simple rule-based system is scripted to govern the behavior of battlespace entities.
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Situation Management [Guest editorial]
IEEE Communications Magazine, 2010Co-Authors: Gabriel Jakobson, John F Buford, Lundy LewisAbstract:Many domains, such as physical infrastructure and cyber security monitoring, battlefield operations Management, disaster response and crisis Management, and homeland security, are characterized by dense realtime sensing, large numbers of distributed heterogeneous information sources, and a variety of distributed, communicating, and network-enabled actors and agents. In these domains there is the need to automatically and continuously identify and act on complex, often incomplete and unpredictable dynamic Situations. As a result, effective methods of Situation recognition, prediction, reasoning, and control are required - operations collectively identifiable as Situation Management.
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Using gaming technologies and platforms to experiment with fusion algorithms for Situation Management
MILCOM 2009 - 2009 IEEE Military Communications Conference, 2009Co-Authors: Lundy Lewis, Tom Adamson, Matt Studley, Mike Faucon, Yanbin Guo, Christopher MelansonAbstract:In this paper we discuss issues in testing various cognitive fusion algorithms for Situation Management. We provide a proof-of-principle discussion and demo showing how gaming technologies and platforms could be used to devise and test various fusion algorithms, including input, processing, and output. We argue that the proof-of-principle warrants further work on more advanced test beds and methods for high-level fusion in support of Situation Management. We develop four simple fusion scenarios and one more complex scenario in which a simple rule-based system is scripted to govern the behavior of battlespace entities.
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Models of feedback and adaptation in multi-agent systems for disaster Situation Management
Sensors and Command Control Communications and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII, 2008Co-Authors: Gabriel Jakobson, John F Buford, Lundy LewisAbstract:The response, rescue and recovery teams that are engaged in disaster Management operations require a continuous and comprehensive information flow of the disaster environment and a Situational awareness in order to undertake fast and coordinated actions. Because of highly dynamic and often unpredictable disaster Situations the teams need to adjust their goals, resources and actions both on an individual member level (agent) and on an entire team level (multi-agent system). This paper investigates a new approach to an agent's adaptability based on cognitive feedback introduced into the framework of inter-agent collaboration. The paper is a continuation of our work on Situation-aware multi-agent systems. We discuss how agent adaptation and cognitive feedback is applied in the architecture of multi-agent systems for disaster Situation Management.
Gabriel Jakobson - One of the best experts on this subject based on the ideXlab platform.
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CogSIMA - On modeling context in Situation Management
2014 IEEE International Inter-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2014Co-Authors: Gabriel JakobsonAbstract:One of the inherit features of cognitive Situation awareness and decision support processes is that they are context-dependent. This is hardly disputed by anybody, but as soon one wants to understand what this context dependency means, or even more, what is context and how it relates to a Situation then we have to admit that no common understanding exists on those categories. The objective of this paper is to analyze the role of context in Situation Management applied to dynamic Situation-driven systems, review the Situation-of the art in understanding context, and outline a basis for a more formal handling of context in Situation Management.
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Peer-to-peer coupled agent systems for distributed Situation Management
Information Fusion, 2010Co-Authors: John F Buford, Gabriel Jakobson, Lundy LewisAbstract:Large scale Situation Management applications such as disaster recovery and network-centric battle Management are characterized by distributed heterogeneous agent platforms with dynamic agent populations, highly variable network connectivity and bandwidth, and localized Situation knowledge and event collection. We describe a new agent model and an integrated peer-to-peer architecture which addresses these requirements. We present an extension of the BDI agent model which allows it to be used in highly reactive applications. We describe the use of multi-hop peer-to-peer overlays which provides highly scalable coupling of distributed agent platforms. Finally, we describe a two-phase semantic discovery mechanism which serves as a basis for agents to share events and Situations across the overlay.
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Incorporating time and spatial-temporal reasoning into Situation Management
Cyber Security Situation Management and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 2010Co-Authors: Gabriel JakobsonAbstract:Spatio-temporal reasoning plays a significant role in Situation Management that is performed by intelligent agents (human or machine) by affecting how the Situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data Management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in Situation Management, particularly how to resolve Situations that are described by using spatio-temporal relations among events and Situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.
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Situation Management [Guest editorial]
IEEE Communications Magazine, 2010Co-Authors: Gabriel Jakobson, John F Buford, Lundy LewisAbstract:Many domains, such as physical infrastructure and cyber security monitoring, battlefield operations Management, disaster response and crisis Management, and homeland security, are characterized by dense realtime sensing, large numbers of distributed heterogeneous information sources, and a variety of distributed, communicating, and network-enabled actors and agents. In these domains there is the need to automatically and continuously identify and act on complex, often incomplete and unpredictable dynamic Situations. As a result, effective methods of Situation recognition, prediction, reasoning, and control are required - operations collectively identifiable as Situation Management.
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Models of feedback and adaptation in multi-agent systems for disaster Situation Management
Sensors and Command Control Communications and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII, 2008Co-Authors: Gabriel Jakobson, John F Buford, Lundy LewisAbstract:The response, rescue and recovery teams that are engaged in disaster Management operations require a continuous and comprehensive information flow of the disaster environment and a Situational awareness in order to undertake fast and coordinated actions. Because of highly dynamic and often unpredictable disaster Situations the teams need to adjust their goals, resources and actions both on an individual member level (agent) and on an entire team level (multi-agent system). This paper investigates a new approach to an agent's adaptability based on cognitive feedback introduced into the framework of inter-agent collaboration. The paper is a continuation of our work on Situation-aware multi-agent systems. We discuss how agent adaptation and cognitive feedback is applied in the architecture of multi-agent systems for disaster Situation Management.
Serge Chaumette - One of the best experts on this subject based on the ideXlab platform.
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ASIMUT project: Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques
2017Co-Authors: Pascal Bouvry, Martin Rosalie, Grégoire Danoy, Serge Chaumette, Gilles Guerrini, Gilles Jurquet, Achim Kuwertz, Wilmuth Müller, Jennifer Sander, Florian SegorAbstract:This document summarizes the activities and results of the ASIMUT project (Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques) carried out by the consortium composed of Thales, Fraunhofer IOSB, Fly-n-Sense, University of Bordeaux and University of Luxembourg. Funded by the European Defence Agency (EDA), the objectives of the ASIMUT project are to design, implement and validate algorithms that will allow the efficient usage of autonomous swarms of Unmanned Aerial Vehicles (UAVs) for surveillance missions.
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DroNet@MobiSys - ASIMUT project: Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques
Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks Systems and Applications - DroNet '17, 2017Co-Authors: Pascal Bouvry, Martin Rosalie, Grégoire Danoy, Serge Chaumette, Gilles Guerrini, Gilles Jurquet, Achim Kuwertz, Wilmuth Müller, Jennifer Sander, Florian SegorAbstract:This document summarizes the activities and results of the ASIMUT project (Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques) carried out by the consortium composed of Thales, Fraunhofer IOSB, Fly-n-Sense, University of Bordeaux and University of Luxembourg. Funded by the European Defence Agency (EDA), the objectives of the ASIMUT project are to design, implement and validate algorithms that will allow the efficient usage of autonomous swarms of Unmanned Aerial Vehicles (UAVs) for surveillance missions.
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Using Heterogeneous Multilevel Swarms of UAVs and High-Level Data Fusion to Support Situation Management in Surveillance Scenarios
2016Co-Authors: Pascal Bouvry, Martin Rosalie, Grégoire Danoy, Serge Chaumette, Gilles Guerrini, Gilles Jurquet, Achim Kuwertz, Wilmuth Müller, Jennifer SanderAbstract:The development and usage of Unmanned Aerial Vehicles (UAVs) quickly increased in the last decades, mainly for military purposes. This technology is also now of high interest in non-military contexts like logistics, environmental studies and different areas of civil protection. While the technology for operating a single UAV is rather mature, additional efforts are still necessary for using UAVs in fleets (or swarms). The Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques (ASIMUT) project which is supported by the European Defence Agency (EDA) aims at investigating and demonstrating dedicated surveillance services based on fleets of UAVs. The aim is to enhance the Situation awareness of an operator and to decrease his workload by providing support for the detection of threats based on multi-sensor multi-source data fusion. The operator is also supported by the combination of information delivered by the heterogeneous swarms of UAVs and by additional information extracted from intelligence databases. As a result, a distributed surveillance system increasing detection, high-level data fusion capabilities and UAV autonomy is proposed.
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UAV Multilevel Swarms for Situation Management
2016Co-Authors: Martin Rosalie, Grégoire Danoy, Serge Chaumette, Pascal BouvryAbstract:The development and usage of Unmanned Aerial Vehicles (UAVs) quickly increased in the last decades, mainly for military purposes. Now, this type of technology is also used in non-military contexts mainly for civil and environment protection: search & rescue teams, fire fighters, police officers, environmental scientific studies, etc. Although the technology for operating a single UAV is now mature, additional efforts are still necessary for using UAVs in fleets (or swarms). Therefore the ASIMUT project (Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques). The major challenge of this project consists in handling several fleets of UAVs including communication, networking and positioning aspects. This motivates the development of novel multilevel cooperation algorithms which have not been widely explored, especially when autonomy is an additional challenge. Techniques to optimize communications for multilevel swarms are also required. Finally, distributed and localized mobility Management algorithms that cope with conflicting objectives such as connectivity maintenance and geographical area coverage must be provided.
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UAV Multilevel Swarms for Situation Management
2016Co-Authors: Martin Rosalie, Grégoire Danoy, Pascal Bouvry, Serge ChaumetteAbstract:The development and usage of Unmanned Aerial Vehicles (UAVs) quickly increased in the last decades, mainly for military purposes. Nowadays, this type of technology is used in non-military contexts mainly for civil and environment protection: search & rescue teams, fire fighters, police officers , environmental scientific studies, etc. Although the technology for operating a single UAV is now mature, additional efforts are still necessary for using UAVs in fleets (or swarms). This position paper presents the ASIMUT project (Aid to Situation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques). The challenges of this project consist of handling several fleets of UAVs including communication, networking and positioning aspects. This motivates the development of novel multilevel cooperation algorithms which is an area that has not been widely explored , especially when autonomy is an additional challenge. Moreover, we will provide techniques to optimize communications for multilevel swarms. Finally, we will develop distributed and localized mobility Management algorithms that will cope with conflicting objectives such as connectiv-ity maintenance and geographical area coverage.