Reference : Fuzzy Logic User Adaptive Navigation Control System For Mobile Robots In Unknown Envi...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/19742
Fuzzy Logic User Adaptive Navigation Control System For Mobile Robots In Unknown Environments
English
Olivares Mendez, Miguel Angel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > > ; Universidad Politecnica de Madrid, Computer Vision Group]
Fernadez Madrigal, Juan Antonio [Universidad de Malaga]
Oct-2007
Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on
Yes
International
Madrid
Spain
IEEE International Symposium on Intelligent Signal Processing, 2007. WISP 2007.
October 2007
[en] adaptive control ; collision avoidance ; fuzzy control ; mobile robots ; navigation ; sensors ; PLS laser sensor ; fuzzy logic user adaptive navigation control system ; fuzzy system ; mobile robots ; obstacle detection/avoidance ; odometry sensors ; robot localization ; robotic wheelchair ; unknown environment ; Adaptive control ; Adaptive systems ; Control systems ; Fuzzy control ; Fuzzy logic ; Mobile robots ; Navigation ; Programmable control ; Robot sensing systems
[en] This paper presents a software implementation of a user adaptive fuzzy control system for autonomous navigation in mobile robots for unknown environments. This system has been tested in a pioneer mobile robot and on a robotic wheelchair, fitted with PLS laser sensor to detect the obstacles and odometry sensors for localization of robots and the goal positions. The system is able to drive the robots to their goal position avoiding static and dynamic obstacles, without using any pre-built map. Our approach learn from user behaviors in the way it can resolve different situations against obstacles or walls.We propose and implement two updates for the fuzzy system. For the implementation of the learning algorithm we use a weighting scheme giving a value for each fuzzy-rule, this value is based on the synapse-weight idea and represent the contribution of each rule in the system output. We also create of a more important sector in the definition of the fuzzy-variables, based on a statistics system that measure the uses of all the sets of the variables in order to contract the size of the rule-base.
http://hdl.handle.net/10993/19742
10.1109/WISP.2007.4447633
1-6

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