Hostname: page-component-7c8c6479df-p566r Total loading time: 0 Render date: 2024-03-28T08:52:04.579Z Has data issue: false hasContentIssue false

Pseudoinverse-type bi-criteria minimization scheme for redundancy resolution of robot manipulators

Published online by Cambridge University Press:  22 May 2014

Bolin Liao*
Affiliation:
College of Information Science and Engineering, Jishou University, Jishou 416000, China
Weijun Liu
Affiliation:
School of Physics and Electronic Information, Gannan Normal University, Ganzhou 341000, China
*
*Corresponding author. Email: mulinliao8184@163.com

Summary

In this paper, a pseudoinverse-type bi-criteria minimization scheme is proposed and investigated for the redundancy resolution of robot manipulators at the joint-acceleration level. Such a bi-criteria minimization scheme combines the weighted minimum acceleration norm solution and the minimum velocity norm solution via a weighting factor. The resultant bi-criteria minimization scheme, formulated as the pseudoinverse-type solution, not only avoids the high joint-velocity and joint-acceleration phenomena but also causes the joint velocity to be near zero at the end of motion. Computer simulation results based on a 4-Degree-of-Freedom planar robot manipulator comprising revolute joints further verify the efficacy and flexibility of the proposed bi-criteria minimization scheme on robotic redundancy resolution.

Type
Articles
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Flash, T., Meirovitch, Y. and Barliya, A., “Models of human movement: Trajectory planning and inverse kinematics studies,” Robot. Auton. Syst. 61 (4), 330339 (2013).Google Scholar
2. Azmy, E. W., “Exact solution of inverse kinematic problem of 6R serial manipulators using Clifford Algebra,” Robotica 31, 417422 (2013).Google Scholar
3. Guigue, A., Ahmadi, M., Langlois, R. and Hayes, M. J. D., “Pareto optimality and multiobjective trajectory planning for a 7-DOF redundant manipulator,” IEEE Trans. Robot. 26 (6), 10941099 (2010).Google Scholar
4. Groh, F., Groh, K. and Verl, A., “On the inverse kinematics of an a priori unknown general 6R-Robot,” Robotica 31, 455463 (2013).Google Scholar
5. Galicki, M., “Path-constrained control of a redundant manipulator in a task space,” Robot. Auton. Syst. 54 (3), 234243 (2006).Google Scholar
6. Kumara, S., Behera, L. and McGinnity, T. M., “Kinematic control of a redundant manipulator using an inverse-forward adaptive scheme with a KSOM-based hint generator,” Robot. Auton. Syst. 58 (5), 622633 (2010).Google Scholar
7. O'Neil, K. A., “Divergence of linear acceleration-based redundancy resolution schemes,” IEEE Trans. Robot. Autom. 18 (4), 625631 (2002).Google Scholar
8. Deo, A. S. and Walker, I. D., “Minimum effort inverse kinematics for redundant manipulators,” IEEE Trans. Robot. Autom. 15 (3), 767775 (1997).Google Scholar
9. Granvagne, I. A. and Walker, I. D., “On the structure of minimum effort solutions with application to kinematic redundancy resolution,” IEEE Trans. Robot. Autom. 16 (6), 855863 (2000).Google Scholar
10. Siciliano, B. and Khatib, O., Springer Handbook of Robotics (Springer-Verlag, Heidelberg, Germany, 2008).Google Scholar
11. Siciliano, B., Sciavicco, L., Villani, L. and Oriolo, G., Robotics: Modelling, Planning and Control (Springer-Verlag, London, 2009).Google Scholar
12. Gosselin, C. and Angeles, J., “Singularity analysis of closed-loop kinematic chains,” IEEE Trans. Rotot. Autom. 6 (3), 281290 (1990).Google Scholar
13. Kemény, Z., “Redundancy resolution in robots using parameterization through null space,” IEEE Trans. Ind. Electron. 50 (4), 777783 (2003).Google Scholar
14. Taghirad, H. D. and Bedoustani, Y. B., “An analytic-iterative redundancy resolution scheme for cable-driven redundant parallel manipulators,” IEEE Trans. Robot. 27 (6), 11371143 (2011).Google Scholar
15. Patchaikani, P. K., Behera, L. and Prasad, G., “A single network adaptive critic-based redundancy resolution scheme for robot manipulators,” IEEE Trans. Ind. Electron. 59 (8), 32413253 (2012).Google Scholar
16. Abe, A., “Trajectory planning for flexible Cartesian robot manipulator by using artificial neural network: Numerical simulation and experimental verification,” Robotica 29, 797804 (2011).Google Scholar
17. Tchon, K., “Optimal extended Jacobian inverse kinematics algorithms for robotic manipulators,” IEEE Trans. Robot. 24 (6), 14401445 (2008).Google Scholar
18. Marcos, M. G., Machado, J. A. T. and Azevedo-Perdicoúlis, T.-P., “A multi-objective approach for the motion planning of redundant manipulators,” Appl. Soft Comput. 12 (2), 589599 (2012).Google Scholar