Fault detection in autonomous robots based on fault injection and learning

Autonomous Robots

Volumn 24, Issue 1, 2008, Pages 49-67

  Christensen, Anders Lyhne ^a   O'Grady, Rehan ^a   Birattari, Mauro ^a   Dorigo, Marco ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

Fault detection; Fault injection; Learning; Mobile robots; Model free

Indexed keywords

ACTUATORS; DATA ACQUISITION; FAULT DETECTION; LEARNING SYSTEMS; NEURAL NETWORKS;

FAULT DETECTORS; FAULT INJECTION; HARDWARE FAULTS; SENSORY DATA;

MOBILE ROBOTS;

EID: 37449022367     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10514-007-9060-9     Document Type: Article

References (43)

1. Arlat, J., Aguera, M., Amat, L., Crouzet, Y., Fabre, J., Laprie, J., Martins, E., & Powell, D. (1990). Fault injection for dependability validation: a methodology and some applications. IEEE Transactions on Software Engineering, 16(2), 166-182.
2. Ashokaraj, I., Tsourdos, A., Silson, P., & White, B. A. (2004). Sensor based robot localisation and navigation: using interval analysis and unscented Kalman filter. In Proceedings of the 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS 2004) (Vol. 1, pp. 64-70). Las Vegas: IEEE Press.
3. Canham, R., Jackson, A., & Tyrrell, A. (2003). Robot error detection using an artificial immune system. In Proceedings of NASA/DoD conference on evolvable hardware (pp. 199-207). Washington: IEEE Computer Society.
4. Carlson, J., & Murphy, R. (2003). Reliability analysis of mobile robots. In Proceedings of IEEE international conference on robotics and automation, ICRA'03 (Vol. 1, pp. 274-281). Los Alamitos: IEEE Computer Society Press.
5. Clouse, D., Giles, C., Horne, B., & Cottrell, G. (1997). Time-delay neural networks: representation and induction of finite-state machines. IEEE Transactions on Neural Networks, 8, 1065-1070.
6. Dearden, R., Hutter, F., Simmons, R., Thrun, S., Verma, V., & Willeke, T. (2004). Real-time fault detection and situational awareness for rovers: report on the Mars technology program task. In Proceedings of IEEE aerospace conference (Vol. 2, pp. 826-840). Los Alamitos: IEEE Computer Society Press.
7. Dias, M. B., Zinck, M. B., Zlot, R. M., & Stentz, A. (2004). Robust multirobot coordination in dynamic environments. In Proceedings of IEEE conference on robotics and automation, ICRA'04 (Vol. 4, pp. 3435-3442). Piscataway: IEEE Press.
8. Dorigo, M., Trianni, V., Şahin, E., Groß, R., Labella, T. H., Baldassarre, G., Nolfi, S., Deneubourg, J.-L., Mondada, F., Floreano, D., & Gambardella, L. M. (2004). Evolving self-organizing behaviors for a swarm-bot. Autonomous Robots, 17(2-3), 223-245.
9. Forrest, S., Perelson, A., Allen, L., & Cherukuri, R. (1994). Self-nonself discrimination in a computer. In Proceedings of the 1994 IEEE symposium on research in security and privacy (Vol. 212, pp. 202-212). Los Alamitos: IEEE Computer Society.
10. Gerkey, B., & Matarić, M. J. (2002a). Pusher-watcher: an approach to fault-tolerant tightly-coupled robot coordination. In Proceedings of IEEE international conference on robotics and automation, ICRA'02 (pp. 464-469). Piscataway: IEEE Press.
11. Gerkey, B. P., & Matarić, M. J. (2002b). Sold!: Auction methods for multirobot coordination. IEEE Transactions on Robotics and Automation, 18(5), 758-768.
12. Gertler, J. J. (1988). Survey of model-based failure detection and isolation in complex plants. IEEE Control Systems Magazine, 8, 3-11.
13. Goel, P., Dedeoglu, G., Roumeliotis, S., & Sukhatme, G. (2000). Fault detection and identification in a mobile robot using multiple model estimation and neural network. In Proceedings of IEEE international conference on robotics and automation, ICRA'00 (Vol. 3, pp. 2302-2309). Los Alamitos: IEEE Computer Society Press.
14. Groß, R., Bonani, M., Mondada, F., & Dorigo, M. (2006). Autonomous self-assembly in swarm-bots. IEEE Transactions on Robotics, 22(6), 1115-1130.
15. Hinchey, M., Rash, J., Rouff, C., & Truszkowski, W. (2004). NASA's swarm missions: the challenge of building autonomous software. IT Professional, 6, 47-52.
16. Hsueh, M., Tsai, T., & Iyer, R. (1997). Fault injection techniques and tools. Computer, 30(4), 75-82.
17. Isermann, R. (1997). Supervision, fault-detection and fault-diagnosis methods-an introduction. Control Engineering Practice, 5(5), 639-652.
18. Isermann, R., & Ballé, P. (1997). Trends in the application of model-based fault detection and diagnosis of technical processes. Control Engineering Practice, 5(5), 709-719.
19. Julier, S. J., & Uhlmann, J. K. (1997). A new extension of the Kalman filter to nonlinear systems. In Proceedings of the 11th international symposium on aerospace/defense sensing, simulation and controls (Vol. 3, pp. 182-193). Bellingham: SPIE.
20. Kalman, R. (1960). A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1), 35-45.
21. Kochan, A. (2005). A bumper year for robots. Industrial Robot: An International Journal, 32, 201-204.
22. Leonard, J. J., & Durrant-Whyte, H. F. (1991). Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation, 7(3), 376-382.
23. Lerner, U., Parr, R., Koller, D., & Biswas, G. (2000). Bayesian fault detection and diagnosis in dynamic systems. In Proceedings of the 7th national conference on artificial intelligence (pp. 531-537). Cambridge: AAAI Press/MIT Press.
24. Lewis, M. A., & Tan, K. H. (1997). High precision formation control of mobile robots using virtual structures. Autonomous Robots, 4(4), 387-403.
25. Li, P., & Kadirkamanathan, V. (2001). Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems. IEEE Transactions Systems, Man Cybernetics, Part C, 31(3), 337-343.
26. Marsland, S., Nehmzow, U., & Shapiro, J. (2005). On-line novelty detection for autonomous mobile robots. Robotics and Autonomous Systems, 51(2-3), 191-206.
27. Mondada, F., Pettinaro, G. C., Guignard, A., Kwee, I., Floreano, D., Deneubourg, J.-L., Nolfi, S., Gambardella, L., & Dorigo, M. (2004). Swarm-bot: a new distributed robotic concept. Autonomous Robots, 17(2-3), 193-221.
28. Mondada, F., Gambardella, L. M., Floreano, D., Nolfi, S., Deneubourg, J.-L., & Dorigo, M. (2005). The cooperation of swarm-bots: physical interactions in collective robotics. IEEE Robots and Automation Magazine, 12(2), 21-28.
29. Nouyan, S., Groß, R., Bonani, M., Mondada, F., & Dorigo, M. (2006). Group transport along a robot chain in a self-organised robot colony. In T. Arai, R. Pfeifer, T. Balch, & H. Yokoi (Eds.), Intelligent autonomous systems (Vol. 9, pp. 433-442). Amsterdam: IOS Press.
30. Nouyan, S., Campo, A., & Dorigo, M. (2008). Path formation in a robot swarm: self-orgenized strategies to find your way home. Swarm Intelligence, 1(2).
31. O'Grady, R., Groß, R., Mondada, F., Bonani, M., & Dorigo, M. (2005). Self-assembly on demand in a group of physical autonomous mobile robots navigating rough terrain. In M. S. Capcarrere, A. A. Freitas, P. J. Bentley, C. G. Johnson, & J. Timmis (Eds.), Lecture notes in artificial intelligence : Vol. 3630. Advances in artificial life: 8th European conference, ECAL 2005 (pp. 272-281). Berlin: Springer.
32. Parker, L. E. (1998). ALLIANCE: an architecture for fault tolerant multirobot cooperation. IEEE Transactions on Robotics and Automation, 14(2), 220-240.
33. Patton, R., Uppal, F., & Lopez-Toribio, C. (2000). Soft computing approaches to fault diagnosis for dynamic systems: a survey. In A. Edelmayer, C. Banyasz (Eds.), Proceedings of 4th IFAC symposium on fault detection supervision and safety for technical processes (Vol. 1, pp. 298-311). Oxford: Elsevier.
34. Roumeliotis, S., Sukhatme, G., & Bekey, G. (1998). Sensor fault detection and identification in a mobile robot. In Proceedings of IEEE/RSJ international conference on intelligent robots and systems (Vol. 3, pp. 1383-1388). Los Alamitos: IEEE Computer Society Press.
35. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by back-propagating errors. Nature, 323, 533-536.
36. Skoundrianos, E. N., & Tzafestas, S. G. (2004). Finding fault-fault diagnosis on the wheels of a mobile robot using local model neural networks. IEEE Robotics and Automation Magazine, 11(3), 83-90.
37. Smith, R., & Cheeseman, P. (1986). On the representation and estimation of spatial uncertainty. The International Journal of Robotics Research, 5(4), 56.
38. Terra, M., & Tinos, R. (2001). Fault detection and isolation in robotic manipulators via neural networks: a comparison among three architectures for residual analysis. Journal of Robotic Systems, 18(7), 357-374.
39. Trianni, V., & Dorigo, M. (2006). Self-organisation and communication in groups of simulated and physical robots. Biological Cybernetics, 95, 213-231.
40. Verma, V., & Simmons, R. (2006). Scalable robot fault detection and identification. Robotics and Autonomous Systems, 54(2), 184-191.
41. Verma, V., Gordon, G., Simmons, R., & Thrun, S. (2004). Real-time fault diagnosis. IEEE Robotics and Automation Magazine, 11(2), 56-66.
42. Vemuri, A., & Polycarpou, M. (1997). Neural-network-based robust fault diagnosis in robotic systems. IEEE Transactions on Neural Networks, 8(6), 1410-1420.
43. Waibel, A., Hanazawa, T., Hinton, G., Shikano, K., & Lang, K. (1989). Phoneme recognition using time-delay neural networks. IEEE Transactions Acoustics, Speech, and Signal Processing, 37, 328-339.