Abstract
In this paper, anti-virus problem and software fault diagnosis of mobile robot, an immune robot, is discussed with proposal of a novel tri-tier immune system (TTIS). TTIS is a novel artificial immune system, which is comprised of three computing tiers and based on the normal model. The three tiers include inherent immune tier, adaptive immune tier and parallel immune tier. The tri-tier immune model is built on some theories of human immune system and has many good features, such as adaptability, immunity, memory, learning, and robustness. At the same time, for such immune robot, a novel normal model for the robot software is also proposed. The normal model is built on the space–time properties of each component in the robot software and can uniquely identify the normal state of the robot software. Such tri-tier immune system based on the normal model is suitable for anti-virus and fault diagnosis, which enable the immune robot to detect all viruses and faults in the robot software, recognize many viruses and faults, eliminate the viruses and faults, and repair the damaged robot software to its normal state. Meanwhile, simulation results show that the tri-tier immune system has the properties of immunity, security and robustness.
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Gong, T. Cai, Z. X.: Mobile immune-robot model. In: Proceedings of IEEE International Conference on Robotics, Intelligent Systems and Signal Processing , 1091–1096 (2003).
Matthias, O.F., Hanspeter, A.M.: Biomimetic robot navigation. Robot. Auton. Syst. 30, (1), 133–153 (2000)
Yu, J.Z., Wang, S., Tan, M.: Basic motion control of a free-swimming biomimetic robot fish. Proc. IEEE Conf. Decis. Control. 2, 1268–1273 (2003)
Jerne, N.K.: Towards a network theory of the immune system. Ann. Immunol. (Paris). 125C, 373(1974)
Deem, M.W., Lee, H.Y.: Sequence space localization in the immune system response to vaccination and disease. Phys. Rev. Lett. 91, (6), 068101/1–4 (2003)
Balthrop, J., Forrest, S., Newman, M.E.J., et al.: Technological networks and the spread of computer viruses. Science, 304, (5670), 527–529 (2004)
Dasgupta, D., González, F.: An immunity-based technique to characterize intrusions in computer networks. IEEE Trans. Evol. Comput. 6, (3), 281–291 (2002)
Harmer, P.K., Williams, P.D., Gunsch, G.H., et al.: An artificial immune system architecture for computer security applications. IEEE Trans. Evol. Comput. 6, (3), 252–280 (2002)
Branco, C.P.J., Mendes, V.R., Dente, J.A.: Using immunology principles for fault detection. IEEE Trans. Ind. Electron. 50, (2), 362–373 (2003)
Luh, G.C., Cheng, W.C.: Identification of immune models for fault detection. Proc. Inst. Mech. Eng., Part I, J. Syst. Control Eng. 218, (5), 353–367 (2004)
Gong, T., Cai, Z.X.: Parallel evolutionary computing and 3-tier load balance of remote mining robot. Trans. Nonferrous. Met. Soc. China. 13, (4), 948–952 (2003)
de Castro, L.N., Timmis, J.: Artificial immune systems as a novel soft computing paradigm. Soft Comput. 7, (8), 526–544 (2003)
de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, London (2002)
Watkins, A., Timmis, J., Boggess, L.: Artificial immune recognition system (AIRS): an immune-inspired supervised learning algorithm. Genetic Programming and Evolvable Machines 5, (3), 291–317 (2004)
Cai, Z.X., Peng, Z.H.: Cooperative coevolutionary adaptive genetic algorithm in path planning of cooperative multi-mobile robot systems. J. Intell. Robot. Syst. 33, 61–71 (2002)
Gong, T., Cai, Z.X.: Anti-worm immunization of web system based on normal model and BP neural network. In: Wang, J., et al. (Eds.) ISNN 2006, LNCS 3973, 267–272 (2006)
Madhusudan, B., Lockwood, J.W.: A hardware-accelerated system for real-time worm detection. IEEE Micro. 25, (1), 60–69 (2005)
Verma, V., Gordon, G., Simmons, R., et al.: Real-time fault diagnosis robot fault diagnosis. IEEE Robot. Autom. Mag. 11, (2), 56–66 (2004)
Huang, G.B., Saratchandran, P., Sundararajan, N.: A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation. IEEE Trans. Neural Netw. 16, (1), 57–67 (2005)
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Gong, T., Cai, Z. Tri-tier Immune System in Anti-virus and Software Fault Diagnosis of Mobile Immune Robot Based on Normal Model. J Intell Robot Syst 51, 187–201 (2008). https://doi.org/10.1007/s10846-007-9186-1
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DOI: https://doi.org/10.1007/s10846-007-9186-1