A comparison of Jacobian-based methods of inverse kinematics for serial robot manipulators

The objective of this paper is to present and make a comparative study of several inverse kinematics methods for serial manipulators, based on the Jacobian matrix. Besides the well-known Jacobian transpose and Jacobian pseudo-inverse methods, three others, borrowed from numerical analysis, are presented. Among them, two approximation methods avoid the explicit manipulability matrix inversion, while the third one is a slightly modified version of the Levenberg-Marquardt method (mLM). Their comparison is based on the evaluation of a short distance approaching the goal point and on their computational complexity. As the reference method, the Jacobian pseudo-inverse is utilized. Simulation results reveal that the modified Levenberg-Marquardt method is promising, while the first order approximation method is reliable and requires mild computational costs. Some hints are formulated concerning the application of Jacobian-based methods in practice.

[1]  Peter Corke Robot Arm Kinematics , 2011 .

[2]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[3]  Leon James Derman Solving the Inverse Kinematics Problem With Genetic Algorithms , 2002 .

[4]  Ignacy Duleba,et al.  On inverting singular kinematics and geodesic trajectory generation for robot manipulators , 1993, J. Intell. Robotic Syst..

[5]  C. S. George Lee,et al.  Robot Arm Kinematics, Dynamics, and Control , 1982, Computer.

[6]  Subhash C. Kak,et al.  Inverse Kinematics in Robotics using Neural Networks , 1999, Inf. Sci..

[7]  Bruno Siciliano,et al.  A closed-loop jacobian transpose scheme for solving the inverse kinematics of nonredundant and redundant wrists , 1989, J. Field Robotics.

[8]  Krzysztof Tchon,et al.  Approximation of Jacobian inverse kinematics algorithms , 2009, Int. J. Appl. Math. Comput. Sci..

[9]  Adi Ben-Israel,et al.  On Iterative Computation of Generalized Inverses and Associated Projections , 1966 .

[10]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[11]  Ignacy Duleba,et al.  Modified Jacobian method of transversal passing through the smallest deficiency singularities for robot manipulators , 2002, Robotica.

[12]  Adi Ben-Israel,et al.  Generalized inverses: theory and applications , 1974 .

[13]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[14]  Ignacy Duleba,et al.  Motion representations for the Lafferriere-Sussmann algorithm for nilpotent control systems , 2011, Int. J. Appl. Math. Comput. Sci..

[15]  Wojciech P. Hunek,et al.  A study on new right/left inverses of nonsquare polynomial matrices , 2011, Int. J. Appl. Math. Comput. Sci..

[16]  Yoshihiko Nakamura,et al.  Advanced robotics - redundancy and optimization , 1990 .

[17]  Andreas C. Nearchou,et al.  Solving the inverse kinematics problem of redundant robots operating in complex environments via a modified genetic algorithm , 1998 .

[18]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[19]  Anthony A. Maciejewski,et al.  The Singular Value Decomposition: Computation and Applications to Robotics , 1989, Int. J. Robotics Res..

[20]  Stefan Schaal,et al.  Learning inverse kinematics , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).