Title :
Fuzzy enhanced advanced genetic algorithm for robot trajectory optimization
Author :
Mahalakshmi, S. ; Sumathi, R.
Author_Institution :
Dept. of Comput. Sci. & Eng., J.J. Coll. of Eng. & Technol., Thiruchirapalli, India
Abstract :
This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (7 dof seriel link robot). The optimization model considers the nonlinear manipulator dynamics, actuator constraints and joint limits. The problem has 2 objective functions, 147 variables and 42 constraints. Fuzzy enhanced advanced Genetic Algorithm namely Fuzzy Differential Evolution Algorithm (FuDE) has been used for the optimization. The trajectories are defined by cubic B-spline functions. The results obtained from FuDE are analyzed.
Keywords :
actuators; fuzzy set theory; genetic algorithms; industrial robots; manipulator dynamics; splines (mathematics); trajectory control; 7 DOF seriel link robot; FuDE; actuator constraints; cubic b-spline functions; fuzzy differential evolution algorithm; fuzzy enhanced advanced genetic algorithm; industrial robot manipulator; joint limits; nonlinear manipulator dynamics; optimization model; robot trajectory optimization; Acceleration; Coal; Manipulators; Optimization; Trajectory; Vectors; Fuzzy enhanced Differential Evolution (FuDE); Multi-objective optimal trajectory planning;
Conference_Titel :
Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on
Conference_Location :
Nagapattinam, Tamil Nadu
Print_ISBN :
978-1-4673-0213-5
