Abstract
In this paper, a sensor data fusion technique is proposed to develop the effective robot navigation and optimize the navigation rules using a Modified Fuzzy Associative Memory (MFAM). MFAM provides good flexibility to use multiple input space and reduction of rule base for robot navigation. The behavior rules obtained from MFAM model are tested using the experimental studies and results are discussed and compared with the existing methods.
Publisher
Trans Tech Publications, Ltd.
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
Reference13 articles.
1. M. Sugeno T. Murofushi, T. Mori, T. Tatematasu, J. Tanaka, Fuzzy Algorithmic Control of a Model Car by Oral Instructions, Fuzzy Sets and Systems, No. 32, pg. 207-219, (1989).
2. F. G. Pin H. Watanabe, J.R. Symon, and R.S. Pattay Using Custom-Designed VLSI Fuzzy Inferencing Chips for the Autonomous Navigation of a Mobile Robot, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, North Carolina, (1992).
3. M. Balzarotti and G. Ulivi. The fuzzy horizon obstacle avoidance method for mobile robots. In Procs. of the world Automation Congress (WAC), vol 3, pg 51-57, TSI press, (1996).
4. A. Ollero, A. Garcia-Cerezo et al. Fuzzy tracking methods for mobile robots chapter 17, Application of fuzzy logics: Towards high machine intelligence quotient systems, prentice hall, New Jersey, (1997).
5. J. Pereira and J. B Bowles. A comparison of PID and fuzzy control of a model car. In Procs. of the IEEE Int. Con. on Fuzzy Systems, pg 849-854, Orlando, FL, (1994).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The Fusion Method of Improvement Bayes for Soccer Robot Vision System;2014 International Symposium on Computer, Consumer and Control;2014-06