LEARNING
Trajectory Tracking of a Mobile Robot Using Fuzzy Logic Tuned by Genetic Algorithm (TECHNICAL NOTE)
Saber Mahboubi, Hossein Nejat Pishkenari, A Alasti
- Year
- 2006
- Citations
- 4
Abstract
In recent years, soft computing methods, like fuzzy logic and neural networks have been presented and developed for the purpose of mobile robot trajectory tracking. In this paper we will present a fuzzy approach to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions and rule weights will be optimized by genetic algorithm in order to obtain more acceptable results. Simulation results have demonstrated significant improvements in controller efficacy.
Keywords
Fuzzy logicTrajectoryMobile robotTracking (education)Controller (irrigation)Computer scienceGenetic algorithmControl theory (sociology)RobotFuzzy control system
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002