DocumentCode
3094029
Title
Notice of Retraction
Simulation on whole inverse kinematics of a 5R robot based on hybrid genetic algorithm
Author
Yong-Gui Zhang ; Li-Ming Xie ; Hao Shen ; Lan Jin
Author_Institution
Key Lab. of Digital Manuf. Technol. & Applic., Lanzhou Univ. of Technol., Lanzhou, China
Volume
3
fYear
2009
fDate
12-15 July 2009
Firstpage
1840
Lastpage
1845
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As the trouble of deriving robot inverse kinematics analytical expression on pose (position & orientation), the complexity of Jacobian matrix and second order influence coefficient matrix of a robot, and the difficulty of calculating inverse Jacobian matrix, the robot simulation of whole inverse kinematics problem on pose, velocity and acceleration is more difficult for a 5R robot. In order to reduce the difficulty, an approach for solving the robot inverse problem of pose, velocity and acceleration has been proposed in this paper, In which the forward pose equation only need to be constructed firstly, and then the forward pose equation and robot link´s velocity and acceleration recursive formulas are employed to calculate joint position, velocity and acceleration using hybrid genetic algorithm (HGA). This can avoid computing inverse Jacobian matrix and the second order influence coefficient matrix, and is proved to be viable by practical computation of a 5R robot inverse whole kinematics.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As the trouble of deriving robot inverse kinematics analytical expression on pose (position & orientation), the complexity of Jacobian matrix and second order influence coefficient matrix of a robot, and the difficulty of calculating inverse Jacobian matrix, the robot simulation of whole inverse kinematics problem on pose, velocity and acceleration is more difficult for a 5R robot. In order to reduce the difficulty, an approach for solving the robot inverse problem of pose, velocity and acceleration has been proposed in this paper, In which the forward pose equation only need to be constructed firstly, and then the forward pose equation and robot link´s velocity and acceleration recursive formulas are employed to calculate joint position, velocity and acceleration using hybrid genetic algorithm (HGA). This can avoid computing inverse Jacobian matrix and the second order influence coefficient matrix, and is proved to be viable by practical computation of a 5R robot inverse whole kinematics.
Keywords
Jacobian matrices; acceleration control; genetic algorithms; robot kinematics; velocity control; 5R robot; acceleration recursive formula; hybrid genetic algorithm; inverse Jacobian matrix; inverse kinematics analytical expression; inverse kinematics simulation; pose equation; second order influence coefficient matrix; velocity control; Acceleration; Cybernetics; Educational robots; Educational technology; Equations; Genetic algorithms; Inverse problems; Jacobian matrices; Machine learning; Robot kinematics; HGA; Inverse acceleration; Inverse kinematics; Inverse velocity; Robot;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Hebei
Print_ISBN
978-1-4244-3702-3
Type
conf
DOI
10.1109/ICMLC.2009.5212328
Filename
5212328
Link To Document