Suo Tan, Simon X. Yang, and Anmin Zhu
[1] R. Siegwart & I.R. Nourbakhsh, Introduction to autonomousmobile robots (London, England: The MIT Press, Cambridge,MA, USA, 2004). [2] P.E. Hart, N.J. Nilsson, & B. Raphael, A formal basis forthe heuristic determination of minimum cost, ACM SIGARTBulletin, 37, 1972, 28–29. [3] D. Ferguson & A. Stentz, Field d: an interpolation-based pathplanner and replanner, Proc. of the Int. Symp. on RoboticsResearch, 2005, 239–253. [4] A. Nash, K. Daniel, S. Koenig, & A. Felner, Theta: any-anglepath planning on grids, Proc. of the AAAI Conf. on ArtificialIntelligence, 2007, 1177–1183. [5] K.H. Kim & H.S. Cho, An obstacle avoidance method formobile robots based on fuzzy decision-making, Robotica, 24,2006, 567–578. [6] A. Zhu & S.X. Yang, A fuzzy logic approach to reactivenavigation of behaviour-based mobile robots, Proc. of IEEEInt. Conf. on Robotics and Automation, 2004, 5045–5050. [7] A. Zhu & S.X. Yang, Neurofuzzy-based approach to mobilerobot navigation in unknown environments, IEEE Transactionson Systems, Man, and Cybernetics, Part C, 37, 2007, 610–621. [8] A. Zhu & S.X. Yang, An adaptive neuro-fuzzy controller forrobot navigation, in W. Yu (Ed.), Recent advances in intellgentcontrol systems (London, UK: Springer-Verlag, 2009), 277–307. [9] W.L. Xu & S.K. Tso, Sensor-based fuzzy reactive navigation of amobile robot through local target switching, IEEE Transactionson Systems, Man, and Cybernetics, Part c, 29(3), 1999, pp.451–459. [10] D.R. Parhi, Navigation of mobile robots using a fuzzy logiccontroller, Journal of Intelligent and Robotic Systems, 42,2005, 253–273. [11] K. Shimojima, T. Fukuda, & Y. Hasegawa, Self-tuning fuzzymodeling with adaptive membership function, rules, and hier-archical structure based on genetic algorithm, Fuzzy Sets andSystems, 71(5), 1995, 295–309. [12] F. Shi & F. Zheng, Optimization of membership function forfuzzy control based on genetic algorithm and its applications,Journal of Shanghai University, 2(4), 1998, pp. 295–300. [13] R. Neves & M. Netto, Evolutionary search for optimization offuzzy logic controllers, FSKD, 2002, 202–206. [14] L. Moreno, J.M. Armingol, S. Garrido, A. Escalera, & M.A.Salichs, A genetic algorithm for mobile robot localization using227ultrasonic sensors, Journal of Intelligent and Robotic Systems,34(2), 2002, 135–154. [15] A. C¸inar, A method for local tuning of fuzzy membershipfunctions, Computational Science, 3516, 2005, 945–949. [16] H. Kawanaka, T. Yoshikawa, & S. Tsuruoka, Acquisition offuzzy control rules for a mobile robot using genetic algorithm,Proc. of the 6th Int. Workshop on Advanced Motion Control,Nagoya, Japan, 2000, 507–512. [17] I. Hassanzadeh & S. Sadigh, Path planning for a mobile robotusing fuzzy logic controller tuned by ga, Proc. of the 6thInt. Symp. on Mechatronics and its Applications (ISMA09),Sharjah, United Arab Emirates, 2009, 1–5. [18] S. Thrun, W. Burgard, & D. Fox, Probabilistic robotics (Lon-don, England: The MIT Press, Cambridge, MA, USA, 2005). [19] S. Tan & S.X. Yang, A fuzzy inference controller with acceler-ate/brake module for mobile robots, Proc. of IEEE Int. Conf.on Automation and Logistics, Qingdao, China, 2008, 810–815. [20] S. Tan, A. Zhu, & S.X. Yang, A ga-based fuzzy logic approachto mobile robot navigation in unknown dynamic environmentswith moving obstacles, Proc. of 2009 IEEE Int. Conf. OnGranular Computing, Nanchang, China, 2009, 629–634. [21] J. Tu, Motion planning and tracking control of a mobile robotusing genetic algorithm based approaches, Masters Thesis,University of Guelph, Guelph, ON, Canada, 2003. [22] F. Herrera, M. Lozano, & J.L. Verdegay, Genetic algorithmsapplications to fuzzy logic based systems, Proc. of 9th Polish-Italian and 5th Polish-Frinish Symposium on System Analysisand Decision Suport in Economics and Technology, 1993, 125–134. [23] M.E. Dupr´e, Ga optimized fuzzy control of an autonomousmobile robot, Masters thesis, University of Guelph, Guelph,ON, Canada, 2007.
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