Decentralised Data Fusion Using Agents

This project investigates aspects of the dynamic control problem where, for example, timeliness, robustness and fault tolerance are critical. An objective is to produce a non-hierarchical structure with the potential for emergent intelligent behaviour, such as would benefit an autonomous vehicle system. Following a general introduction, there is an extensive and detailed discussion of the theories and ideas which support the concept of decentralised data fusion, and the use of agents, while also providing the rationale for subsequent work. This leads to the development of two models. One of these acts as a test-bed to provide data for subsequent analyses. The other is a model which implements data fusion using agents. The two models are linked through an interface called MACSim. MACSim is developed to enable communication between Simulink and JADE, thus bringing together two powerful software tools for modelling the hardware of real-time systems and multi-agent systems. This will facilitate future research and development on decentralised data fusion systems using multiple agents. In the present project a Boeing 747 sensor system is modelled using Simulink. Boeing 747 sensor data is then used to test the operation of an agent-mediated decentralised data fusion system. A variety of experiments are described with detailed discussion of the results obtained. The findings demonstrate the successful implementation of Simulink and JADE operating together. In addition, the results confirm that the performance of a decentralised fusion process, using information filters, can be comparable with a centralised fusion process using Kalman filters. Throughout the testing process there is comparison of three different forms of information filter. The report concludes with a detailed discussion of implications for future research and for further development of the models employed.

[1]  C. C. Heyde,et al.  Central Limit Theorem , 2006 .

[2]  Munindar P. Singh Multiagent Systems - A Theoretical Framework for Intentions, Know-How, and Communications , 1994, Lecture Notes in Computer Science.

[3]  Arthur G. O. Mutambara,et al.  Decentralized Estimation and Control for Multisensor Systems , 2019 .

[4]  Yong Xun,et al.  Control based sensor management for a multiple radar monitoring scenario , 2004, Inf. Fusion.

[5]  Ning Xiong,et al.  Multi-sensor management for information fusion: issues and approaches , 2002, Inf. Fusion.

[6]  Yoav Shoham,et al.  Agent-Oriented Programming , 1992, Artif. Intell..

[7]  David J. Israel,et al.  Plans and resource‐bounded practical reasoning , 1988, Comput. Intell..

[8]  Miguel Peris,et al.  Distributed expert system for the monitoring and control of chemical processes , 1998 .

[9]  A. Gad,et al.  Multitarget Tracking in a Multisensor Multiplatform Environment , 2004 .

[10]  Michael P. Wellman,et al.  Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems , 2006, AAMAS 2006.

[11]  E. Gelenbe,et al.  Simulating the Navigation and Control of Autonomous Agents ∗ , 2004 .

[12]  José Barata,et al.  DSAAR: A Distributed Software Architecture for Autonomous Robots , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[13]  Frank L. Lewis,et al.  Aircraft Control and Simulation , 1992 .

[14]  Pattie Maes,et al.  Situated agents can have goals , 1990, Robotics Auton. Syst..

[15]  Lucy Y. Pao,et al.  Controlling target estimate covariance in centralized multisensor systems , 1998, Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207).

[16]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[17]  Xiaodong Wang,et al.  Decentralized sigma-point information filters for target tracking in collaborative sensor networks , 2005, IEEE Transactions on Signal Processing.

[18]  Gregory J. Pottie,et al.  Entropy-based sensor selection for localization. , 2003 .

[19]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[20]  W. Komorniczak,et al.  Selected problems of MFR resources management , 2000, Proceedings of the Third International Conference on Information Fusion.

[21]  R. T. H.,et al.  The Encyclopaedia Britannica , 1902, Nature.

[22]  Lucy Y. Pao,et al.  Control of sensor information in distributed multisensor systems , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[23]  Christophe Andrieu,et al.  Particle methods for change detection, system identification, and control , 2004, Proceedings of the IEEE.

[24]  Henry Y. K. Lau,et al.  A BIO-INSPIRED MULTI-AGENT CONTROL FRAMEWORK , 2005 .

[25]  Weiming Shen,et al.  Distributed control architecture for collaborative physical robot agents , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[26]  Feng Zhao,et al.  Information-driven dynamic sensor collaboration , 2002, IEEE Signal Process. Mag..

[27]  R.C. Hayward,et al.  Design of multi-sensor attitude determination systems , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[28]  Timothy W. Bickmore,et al.  A basic agent , 1990, Comput. Intell..

[29]  Kenneth J. Hintz,et al.  Information instantiation in sensor management , 1998, Defense, Security, and Sensing.

[30]  Feng He,et al.  An Urban Traffic Control System Based on Mobile Multi-Agents , 2006, 2006 IEEE International Conference on Vehicular Electronics and Safety.

[31]  B. Habibi,et al.  Pengi : An Implementation of A Theory of Activity , 1998 .

[32]  S. Rogers,et al.  Sensor noise fault detection , 2003, Proceedings of the 2003 American Control Conference, 2003..

[33]  Bruno Jouvencel,et al.  Sensor selection in a fusion process: a fuzzy approach , 1994, Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems.

[34]  Robert C. Moore A Formal Theory of Knowledge and Action , 1984 .

[35]  Leslie Pack Kaelbling,et al.  Action and planning in embedded agents , 1990, Robotics Auton. Syst..

[36]  S. Sitharama Iyengar,et al.  Distributed multi-resolution data integration using mobile agents , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[37]  Kurt Sundermeyer,et al.  Cooperative problem-solving guided by intentions and perception (abstract) , 1992, SIGO.

[38]  P. Lima,et al.  Bayesian Sensor Fusion for Cooperative Object Localization and World Modeling , 2003 .

[39]  Futoshi Kobayashi,et al.  Sensor selection based on fuzzy inference for sensor fusion , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[40]  Keum-Shik Hong,et al.  Decentralized information filter in federated form , 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[41]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[42]  David Naso,et al.  A coordination strategy for distributed multi-agent manufacturing systems , 2004 .

[43]  Michael Fisher,et al.  A Survey of Concurrent METATEM - the Language and its Applications , 1994, ICTL.

[44]  J. L. Roux An Introduction to the Kalman Filter , 2003 .

[45]  Jau-Hsiung Wang Fuzzy Logic Expert Rule-based Multi-Sensor Data Fusion for Land Vehicle Attitude Estimation , 2005 .

[46]  Stephen E. Russek,et al.  Low-frequency noise measurements on commercial magnetoresistive magnetic field sensors , 2005 .

[47]  Reid G. Smith,et al.  The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver , 1980, IEEE Transactions on Computers.

[48]  Leslie Pack Kaelbling,et al.  A situated-automata approach to the design of embedded agents , 1991, SGAR.

[49]  Feng Zhao,et al.  Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[50]  João Manuel R. S. Tavares,et al.  Efficient approximation of the Mahalanobis distance for tracking with the Kalman filter , 2006, CompIMAGE.

[51]  Claire J. Tomlin,et al.  Distributed Cooperative Search using Information-Theoretic Costs for Particle Filters, with Quadrotor Applications ∗ , 2006 .

[52]  Vijay Kumar,et al.  Anonymous Cooperation in Robotic Sensor Networks , 2004 .

[53]  E. Nebot,et al.  Autonomous Navigation and Map building Using Laser Range Sensors in Outdoor Applications , 2000 .

[54]  Shmuel Merhav Aerospace Sensor Systems and Applications , 1998 .

[55]  Michael D. Lemmon,et al.  Robust performance of soft real-time networked control systems with data dropouts , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[56]  William A. Maul,et al.  Sensor Selection and Optimization for Health Assessment of Aerospace Systems , 2007, J. Aerosp. Comput. Inf. Commun..

[57]  Marc Rauw,et al.  FDC 1.2 - A Simulink Toolbox for Flight Dynamics and Control Analysis , 2001 .

[58]  E. Glenn Lightsey,et al.  GPS/INS Kalman filter design for spacecraft operating in the proximity of the international space station , 2003 .

[59]  Forlano George An Experiment in Coöperation , 1932 .

[60]  C. Butler,et al.  An experiment in cooperation. , 1969, Nursing outlook.

[61]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[62]  Demoz Gebre-Egziabher,et al.  Design and performance analysis of a low-cost aided dead reckoning navigator , 2001 .

[63]  Tim Clarke,et al.  MACSIM: A SIMULINK ENABLED ENVIRONMENT FOR MULTI-AGENT SYSTEM SIMULATION , 2005 .

[64]  I. Kominis Sub-shot-noise magnetometry with a correlated spin-relaxation dominated alkali-metal vapor. , 2007, Physical review letters.

[65]  Jeffrey K. Uhlmann,et al.  Using covariance intersection for SLAM , 2007, Robotics Auton. Syst..

[66]  Pawel Kaczmarek,et al.  Testing the efficiency of JADE agent platform , 2004, Third International Symposium on Parallel and Distributed Computing/Third International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Networks.

[67]  A. Hero,et al.  INFORMATION-BASED SENSOR MANAGEMENT FOR SIMULTANEOUS MULTITARGET TRACKING AND IDENTIFICATION , 2005 .

[68]  Michael Wooldridge,et al.  A First-Order Branching Time Logic of Multi-Agent System , 1992, ECAI.

[69]  Greg Welch,et al.  SCAAT: incremental tracking with incomplete information , 1997, SIGGRAPH.

[70]  Steen Kristensen,et al.  Sensor Planning With Bayesian Decision Analysis , 1995 .

[71]  G. G. Mannella Aerospace sensor systems. , 1968 .

[72]  Hugh F. Durrant-Whyte,et al.  The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications , 2001, IEEE Trans. Robotics Autom..

[73]  Pattie Maes,et al.  The Dynamics of Action Selection , 1989, IJCAI.

[74]  Guanrong Chen,et al.  Introduction to random signals and applied Kalman filtering, 2nd edn. Robert Grover Brown and Patrick Y. C. Hwang, Wiley, New York, 1992. ISBN 0‐471‐52573‐1, 512 pp., $62.95. , 1992 .

[75]  Jörg P. Müller,et al.  Modelling Interacting Agents in Dynamic Environments , 1994, ECAI.

[76]  Hugh Durrant-Whyte,et al.  Data Fusion and Sensor Management: A Decentralized Information-Theoretic Approach , 1995 .

[77]  Amy L. Lansky,et al.  Reactive Reasoning and Planning , 1987, AAAI.

[78]  Leslie Pack Kaelbling,et al.  The Synthesis of Digital Machines With Provable Epistemic Properties , 1986, TARK.

[79]  Alexei Makarenko,et al.  Decentralised Data Fusion And Control In Active Sensor Networks , 2004 .

[80]  Bala M. Balachandran,et al.  Development of a Multi-Agent System for Travel Industry Support , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).

[81]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[82]  Gregory A. McIntyre,et al.  A Comprehensive Approach to Sensor Management and Scheduling , 1998 .

[83]  Nicholas R. Jennings,et al.  A Roadmap of Agent Research and Development , 2004, Autonomous Agents and Multi-Agent Systems.

[84]  Adrian Schumacher,et al.  Integration of a GPS aided Strapdown Inertial Navigation System for Land Vehicles , 2006 .

[85]  H. Durrant-Whyte,et al.  Data Fusion in Decentralised Sensing Networks , 2001 .

[86]  R. P. G. Collinson,et al.  Introduction to Avionics Systems , 2003 .

[87]  Michael Wooldridge,et al.  The logical modelling of computational multi-agent systems , 1992 .

[88]  Innes A. Ferguson TouringMachines: an architecture for dynamic, rational, mobile agents , 1992 .

[89]  Pattie Maes,et al.  The agent network architecture (ANA) , 1991, SGAR.

[90]  G. Fedder,et al.  Fabrication, characterization, and analysis of a DRIE CMOS-MEMS gyroscope , 2003 .

[91]  D. Gebre‐Egziabher,et al.  DESIGN AND PERFORMANCE ANALYSIS OF A LOW-COST AIDED DEAD RECKONING NAVIGATION SYSTEM , 2001 .

[92]  Sven Sandow,et al.  Learning Probabilistic Models: An Expected Utility Maximization Approach , 2003, J. Mach. Learn. Res..

[93]  Elizabeth A. Croft,et al.  Sensor uncertainty management for an encapsulated logical device architecture: Part I - fusion of uncertain sensor data , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[94]  Warren Flenniken Modeling Inertial Measurement Units and Anlyzing the Effect of Their Errors in Navigation Applications , 2005 .

[95]  Keith L. Clark,et al.  April - Agent PRocess Interaction Language , 1995, ECAI Workshop on Agent Theories, Architectures, and Languages.

[96]  Jie Yang,et al.  Sensor Fusion Using Dempster-Shafer Theory , 2002 .

[97]  Maarten J. Korsten,et al.  Systematic sensor selection for measurement systems , 2001 .

[98]  Kuo-Chu Chang,et al.  Architectures and algorithms for track association and fusion , 2000 .

[99]  Sarah Rebecca Thomas,et al.  PLACA, an agent oriented programming language , 1993 .

[100]  Anand S. Rao,et al.  Asymmetry Thesis and Side-Effect Problems in Linear-Time and Branching-Time Intention Logics , 1991, IJCAI.

[101]  Stanley J. Rosenschein,et al.  Formal theories of knowledge in AI and robotics , 1986, New Generation Computing.

[102]  Keith D. Kastella,et al.  Foundations and Applications of Sensor Management , 2010 .

[103]  Rudolph van der Merwe,et al.  Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[104]  N. Gindy,et al.  Error reduction for an inertial-sensor-based dynamic parallel kinematic machine positioning system , 2003 .

[105]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[106]  Mark Johnson Photodetection and Measurement: Maximizing Performance in Optical Systems , 2003 .

[107]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[108]  F. Daum Nonlinear filters: beyond the Kalman filter , 2005, IEEE Aerospace and Electronic Systems Magazine.

[109]  Eero P. Simoncelli,et al.  Differentiation of discrete multidimensional signals , 2004, IEEE Transactions on Image Processing.

[110]  Beom-Hee Lee,et al.  A KNOWLEDGE BASE FOR DYNAMIC PATH PLANNING OF MULTI-AGENTS , 2005 .

[111]  David Sislák,et al.  Autonomous agents for air-traffic deconfliction , 2006, AAMAS '06.

[112]  Ben Grocholsky,et al.  Information-Theoretic Control of Multiple Sensor Platforms , 2002 .

[113]  Nagarajan Kandasamy,et al.  Sensor selection and placement for failure diagnosis in networked aerial robots , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[114]  James Diebel,et al.  Representing Attitude : Euler Angles , Unit Quaternions , and Rotation Vectors , 2006 .

[115]  Thiagalingam Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation , 2001 .