Adaptive data-driven error detection in swarm robotics with statistical classifiers

Robotics and Autonomous Systems

Volumn 59, Issue 12, 2011, Pages 1021-1035

  Lau, Huikeng ^a,b   Bate, Iain ^a   Cairns, Paul ^a   Timmis, Jon ^a  

^a UNIVERSITY OF YORK   (United Kingdom)

^b UNIVERSITI MALAYSIA SABAH   (Malaysia)

Author keywords

Adaptive error detection; Statistical error detection; Swarm robotics

Indexed keywords

CLASSICAL APPROACH; DATA-DRIVEN; DISTRIBUTED AUTONOMOUS ROBOTS; DYNAMIC ENVIRONMENTS; GLOBAL PERFORMANCE; ROBOTIC SWARMS; STATISTICAL CLASSIFIER; STATISTICAL ERROR DETECTION; STATISTICAL TECHNIQUES; SWARM ROBOTICS; TIME VARYING;

BEHAVIORAL RESEARCH; CLASSIFICATION (OF INFORMATION); ROBOTICS; ROBOTS;

ERROR DETECTION;

EID: 80053560755     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.robot.2011.08.008     Document Type: Article

References (30)

1. E. ahin Swarm robotics: From sources of inspiration to domains of application E. ahin, W. Spears, Proc. 1st Int. Workshop Swarm Robotics 2004 2005 Springer 10 20
2. L. Bayindir, and E. ahin A review of studies in swarm robotics Turkish Journal of Electrical Engineering and Computer Sciences 15 2 2007 115 147 (Pubitemid 47112633)
3. E. ahin, S. Girgin, L. Bayindir, and A. Turgut Swarm robotics C. Blum, D. Merkle, Swarm Intelligence: Introduction and Applications Natural Computing Series 2008 Springer 87 100
4. A.F.T. Winfield, and J. Nembrini Safety in numbers: Fault tolerance in robot swarms International Journal of Modelling, Identification and Control 1 1 2006 30 37
5. J. Timmis, A. Tyrrell, M. Mokhtar, A. Ismail, N. Owens, and R. Bi An artificial immune system for robot organisms P. Levi, S. Kernbach, Symbiotic Multi-Robot Organisms: Reliability, Adaptability and Evolution 2010 Springer 268 288
6. A. Aviienis, Design of fault-tolerant computers, in: Proceedings of the 1967 Fall Joint Computer Conference, 1967, pp. 733743.
7. A.L. Christensen, Fault detection in autonomous robots, Ph.D. Dissertation.
8. R. Oates, J. Greensmith, U. Aickelin, J.M. Garibaldi, and G. Kendall The application of a dendritic cell algorithm to a robotic classifier Proc. 6th Int. Conf. Artificial Immune Systems 2007 Springer 204 215
9. R. Canham, A.H. Jackson, and A. Tyrrell Robot error detection using an artificial immune system Proc. 2003 NASA/DoD Conf. on Evolvable Hardware 2003 IEEE 91 100
10. M. Mokhtar, J. Timmis, A. Tyrrell, and R. Bi A modified dendritic cell algorithm for on-line error detection in robotic system Proc. Congress on Evol. Comput. 2009 2009 IEEE Press 2055 2062
11. L. Festinger A theory of social comparison processes Human Relations 7 2 1954 117 140
12. R. Bi, J. Timmis, and A. Tyrrell The diagnostic dendritic cell algorithm for robotic systems Proc. World Congress on Comput. Intell. 2010 2010 IEEE Press 4280 4289
13. A. Winfield Foraging robots R. Meyers, Encyclopedia of Complexity and System Science 2009 Springer 3682 3700 10.1007/978-0-387-30440-3217
14. R. Brooks A robust layered control system for a mobile robot IEEE Journal of Robotics and Automation 2 1 1986 14 23 (Pubitemid 16576274)
15. W. Liu, Design and modelling of adaptive foraging in swarm robotic systems, Ph.D. Thesis, University of the West of England, 2008.
16. B. Gerkey, R.T. Vaughan, A. Howard, The player/stage project: tools for multi-robot and distributed sensor systems, in: Proc. 11th Int. Conf. Advanced Robotics, 2003, pp. 317323.
17. R.D. Gibbons Statistical Methods for Groundwater Monitoring 1994 John Wiley & Sons, Inc.
18. N. Owens, A. Greensted, J. Timmis, and A. Tyrell T cell receptor signalling inspired kernel density estimation and anomaly detection P. Andrews, J. Timmis, N.D. Owens, U. Aickelin, E. Hart, A. Tyrell, Proc. 8th Int. Conf. Artificial Immune Systems 2009 Springer 122 135
19. N.D. Owens, From biology to algorithms, Ph.D. Thesis, University of York, 2010.
20. F.E. Grubbs Procedures for detecting outlying observations in samples Technometrics 11 1 1969 1 21
21. V.J. Hodge, and J. Austin A survey of outlier detection methodologies Artificial Intelligence Review 22 2004 85 126
22. W. Trochim, and J.P. Donnelly The Research Methods Knowledge Base 2007 Atomic Dog Publishing
23. J.W. Tukey Exploratory Data Analysis 1977 Addison-Wesley
24. NIST/SEMATECH, e-handbook of statistical methods, 2010. URL: http://www.itl.nist.gov/div898/handbook/ [Online; accessed 16.11.10].
25. N. Owens, J. Timmis, A. Greensted, and A. Tyrell Modelling the tunability of early T cell signalling events P. Bentley, D. Lee, S. Jung, Proc. 7th Int. Conf. Artificial Immune Systems 2008 Springer 12 23
26. N.D. Owens, J. Timmis, A. Greensted, and A. Tyrrell Elucidation of T cell signalling models Journal of Theoretical Biology 262 3 2010 452 470
27. J.A. Hilder, N.D.L. Owens, Peter J. Hickey, S.N. Cairns, D.P.A. Kilgour, J. Timmis, and A.M. Tyrrell Parameter optimisation in the receptor density algorithm Proc. 11th Int. Conf. Artificial Immune Systems 2011 Springer 226 239
28. B. Matthews Comparison of the predicted and observed secondary structure of t4 phage lysozyme Biochimica et Biophysica Acta 405 1975 442 451
29. A.L. Christensen, R. O'Grady, M. Birattari, M. Dorigo, Automatic synthesis of fault detection modules for mobile robots, in: Proc. 2nd NASA/ESA Conf. Adaptive Hardware and Syst., 2007, pp. 693700.
30. L. Doherty, B.A. Warneke, B.E. Boser, and K. Pister Energy and performance considerations for smart dust International Journal of Parallel and Distributed Systems and Networks 4 3 2001 121 133 (Pubitemid 33060779)