Abstract
To solve the path planning in complicated environments, an improved artificial immune network strategy for robot path planning is presented. Taking the environment surrounding the robot and robot action as antigen and antibody respectively, an artificial immune network is constructed through the stimulation and suppression between the antigen and antibody, and the optimal path is searched in the network. To further improve the convergence property of immune network, the planning results of artificial potential field (APF) method is taken as the prior knowledge, and the instruction definition of new antibody is initialized through the vaccine extraction and inoculation. The accessibility of proposed improved immune network algorithm (IINA) is analyzed using the Markov chain theory. Compared with simple immune network algorithm (SINA) and ant colony algorithm (ACA), simulation results indicate that the proposed algorithm is characterized by high convergence speed, short planning path and self-learning, which solves the path planning well in complicated environments.
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Ge, S.S., Cui, Y.J.: Dynamic motion planning for mobile robots using potential field method. Auton. Robots. 13(3), 207–222 (2002). doi:10.1023/A:1020564024509
Liu, J., Yang, D.Y.: Path planning based on double-layer genetic algorithm. In: Proceeding of the Third International Conference on Natural Computation, pp. 357–361 (2007)
Liu, G.Q., Li, T.J., Li, Y.P.: The ant algorithm for solving robot path planning problem. In: Proceeding of the Third International Conference on Information Technology and Applications, pp. 25–27 (2005)
Jiao, L.C., Du, H.F.: Development and prospect of the artificial immune system. Acta Electron. Sin. 31(10), 1540–1548 (2003)
Dasgupta, D.: Artificial neural networks and artificial immune systems: similarities and differences. In: Proceeding of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 873–878 (1997)
Farmer, J.D., Packard, N.H., Perelson, A.S.: The immune system, adaptation and machine learning. Physica D. 2(2), 187–204 (1986). doi:10.1016/0167-2789(86)90240-X
Ishiguro, A., Watanabe, Y., Uchikawa, Y.: An immunological approach to dynamic behavior control for autonomous mobile robots. In: Proceeding of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 495–500 (1995)
Ishiguro, A., Watanabe, Y., Kondo, T.: Decentralized consensus-making mechanisms based on immune system-application to a behavior arbitration of an autonomous mobile robot. In: Proceeding of the IEEE International Conference on Evolutionary Computation, pp. 82–87 (1996)
Meshref, H., VanLandingham, H.: Artificial immune systems: application to autonomous agents. In: Proceeding of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 61–66 (2000)
Li, J.H., Wang, S.A.: Model of immune agent and application in path finding of autonomous robots. In: Proceeding of the IEEE International Conference on Machine Learning and Cybernetics, pp. 1961–1964 (2003)
Wang, S.A., Zhuan, J.: An immunity algorithm for path finding and optimizing of the moving robot. J. Syst. Simul. 14(8), 995–997 (2002)
Jerne, N.K.: The immune system. Sci. Am. 229(1), 52–60 (1973)
Jerne, N.K.: Idiotypic networks and other preconceived ideas. Immunol. Rev. 79, 5–24 (1984). doi:10.1111/j.1600-065X.1984.tb00484.x
Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Rob. Res. 5(1), 90–98 (1986). doi:10.1177/027836498600500106
Ge, S.S., Cui, Y.J.: New potential functions for mobile robot path planning. IEEE Trans. Robot. Autom. 16(5), 615–620 (2000). doi:10.1109/70.880813
Zhuang, J., Wang, S.A.: Further study of robot path planning algorithm based on artificial immune net theory. J. Syst. Simul. 16(5), 1017–1019 (2004)
Wang, L.: Kinematics modeling and study for path tracking of track robot. Dissertation, Inner Mongolia University of Technology (2007)
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Yuan, M., Wang, Sa., Wu, C. et al. A Novel Immune Network Strategy for Robot Path Planning in Complicated Environments. J Intell Robot Syst 60, 111–131 (2010). https://doi.org/10.1007/s10846-010-9408-9
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DOI: https://doi.org/10.1007/s10846-010-9408-9