Title :
Robot inverse acceleration solution based on hybrid genetic algorithm
Author :
Zhang, Yong-gui ; Huang, Yu-Mei ; Xie, Li-ming
Author_Institution :
Key Lab. of Digital Manuf. Technol. & Applic., Lanzhou Univ. of Technol., Lanzhou
Abstract :
As the complexity of Jacobian matrix and the second order influence coefficient matrix of a robot, and the difficulty of calculating inverse Jacobian matrix, the problem of solving inverse acceleration is more difficult for a robot with degrees-of-freedom (DOFs) less than 6. Aimed at this problem, an approach for solving the robot inverse acceleration problem has been proposed in this paper, In which the hybrid genetic algorithm (HGA) and robot linkpsilas velocity and acceleration recursive formulas are employed to avoid calculation of inverse Jacobian matrix and the second order influence coefficient matrix. It is proved to be viable by practical computation of a 5-DOF robot inverse acceleration.
Keywords :
Jacobian matrices; acceleration control; genetic algorithms; robots; acceleration recursive formulas; degrees-of-freedom; hybrid genetic algorithm; inverse Jacobian matrix complexity; robot inverse acceleration solution; robot link velocity formulas; second order influence coefficient matrix; Acceleration; Cybernetics; Differential equations; Educational robots; Educational technology; Genetic algorithms; Jacobian matrices; Machine learning; Orbital robotics; Robot kinematics; Acceleration recursion; Hybrid genetic algorithm; Inverse acceleration solution; Robot; Velocity recursion;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620752