Neural Networks Approaches for Computing the Forward Kinematics of a Redundant Parallel Manipulator
In this paper, different approaches to solve the
forward kinematics of a three DOF actuator redundant hydraulic
parallel manipulator are presented. On the contrary to series
manipulators, the forward kinematic map of parallel manipulators
involves highly coupled nonlinear equations, which are almost
impossible to solve analytically. The proposed methods are using
neural networks identification with different structures to solve the
problem. The accuracy of the results of each method is analyzed in
detail and the advantages and the disadvantages of them in
computing the forward kinematic map of the given mechanism is
discussed in detail. It is concluded that ANFIS presents the best
performance compared to MLP, RBF and PNN networks in this
particular application.
[1] J.P. Merlet, Still a long way to go on the road for parallel
mechanisms, ASME 2002 DETC Conference, Montreal, Canada,
2002. Available: http://www-sop.inria.fr.
[2] J.P. Merlet, Parallel Robots: Open problems, In 9th Int'l. Symp. of
Robotics Research, Snowbird, 9-12 October 1999. Available:
http://www-sop.inria.fr.
[3] O.Didrit, M.Petitot and E.Walter, Guaranteed solution of direct
kinematic problems for general configurations of parallel
manipulators, IEEE Trans. On Robotics & Automation, April 1998,
259-266.
[4] B. Dasgupta, T.S. Mruthyunjaya, The Stewart platform manipulator:
a review, Elsevier Science, Mechanism & Machine theory,2000,15-
40.
[5] Hayward, V.: "Design of a hydraulic robot shoulder based on a
combinatorial mechanism" Experimental Robotics III: The 3rd Int'l
Symposium, Japan Oct. 1994. Lecture Notes in Control &
Information Sciences, Springer-Verlag, 297-310.
[6] Hayward, V.: "Borrowing some design ideas from biological
manipulators to design an artificial one" in Robots and Biological
System, NATO Series, Springer-Verlag, 1993, 135-148.
[7] Hayward, V. and Kurtz, R.: Modeling of a parallel wrist mechanism
with actuator redundancy, Int'l. J. Laboratory Robotics and
Automation, VCH Publishers, Vol. 4, No. 2.1992, 69-76.
[8] Z.Geng and L.Haynes, Neural network solution for the forward
kinematics problem of a Stewart platform, Proc. Of the 1991 IEEE
Int'l Conf. on Robotics & Automation, California, April 1991, 2650-
2655.
[9] C.S.Yee and Kah-bin Lim, Forward kinematics solution of Stewart
platform using neural networks, Elsevier Science, Neurocomputing
16, 1997, 333-349.
[10] Nguyen, L., Patel, R.V. and Khorasani, K.: Neural Network
Architectures for the forward kinematics problem in robotics. In
Proc. of the Joint IEEE International Conference on Neural
Networks, San Diego, 1990, 393-399.
[11] D.Wang and A.Zilouchian, Solutions of kinematics of robot
manipulators using a kohonen self organizing neural network, Proc.
Of the 1997 IEEE Int'l Symp. on intelligent control, Turkey, July
1997, 251-255.
[12] L.H.Sang and M.C.Han, The Estimation for forward kinematic
solution of Stewart platform using the neural network, Proc. Of the
1999 IEEE/RSJ Int'l Conf. on Intelligent Robots & Systems, 1999,
501-506.
[13] Lee, S. and Kil, R.M.: Robot kinematic control based on
bidirectional mapping neural network. ," in Proc. IJCNN, San Diego,
CA, Vol. 3, 1990, 327-335.
[14] Ivakhnenko AG. Polynomial theory of complex systems. IEEE
Trans. Systems, Man, Cybernetics, 1971, SMC-1, 364-378.
[15] S.K. Oh, W. Pedrycz, B.J. Park, Polynomial neural networks
architecture: analysis & design, Information Sciences 141, 2002,
237-258.
[16] C.Y. Tsai, An iterative feature reduction algorithm for probabilistic
neural networks, the International Journal of Management Science,
Omega 28, 2000, 513-524.
[17] C.L. Philip chen and A.D. Mc Aulary, Robot kinematics Learning
computatons using polynomial neural networks, proceeding of the
1991 IEEE International conference on Robotics and Automation,
1991, 2638-2643.
[18] R. Boudreau, S. Darenfed, On the computation of the Direct
kinematics of parallel Maniputators using polynomial networks,
IEEE transactions on systems, man and cybernetics, Vol. 28, No. 2,
March 1998, 213-220.
[19] J.R. Jang, "ANFIS: Adaptive-network-based fuzzy inference
system," IEEE Transaction on systems, man and cybernetics, Vol.
23, No. 3, May/June 1993, 665-685.
[1] J.P. Merlet, Still a long way to go on the road for parallel
mechanisms, ASME 2002 DETC Conference, Montreal, Canada,
2002. Available: http://www-sop.inria.fr.
[2] J.P. Merlet, Parallel Robots: Open problems, In 9th Int'l. Symp. of
Robotics Research, Snowbird, 9-12 October 1999. Available:
http://www-sop.inria.fr.
[3] O.Didrit, M.Petitot and E.Walter, Guaranteed solution of direct
kinematic problems for general configurations of parallel
manipulators, IEEE Trans. On Robotics & Automation, April 1998,
259-266.
[4] B. Dasgupta, T.S. Mruthyunjaya, The Stewart platform manipulator:
a review, Elsevier Science, Mechanism & Machine theory,2000,15-
40.
[5] Hayward, V.: "Design of a hydraulic robot shoulder based on a
combinatorial mechanism" Experimental Robotics III: The 3rd Int'l
Symposium, Japan Oct. 1994. Lecture Notes in Control &
Information Sciences, Springer-Verlag, 297-310.
[6] Hayward, V.: "Borrowing some design ideas from biological
manipulators to design an artificial one" in Robots and Biological
System, NATO Series, Springer-Verlag, 1993, 135-148.
[7] Hayward, V. and Kurtz, R.: Modeling of a parallel wrist mechanism
with actuator redundancy, Int'l. J. Laboratory Robotics and
Automation, VCH Publishers, Vol. 4, No. 2.1992, 69-76.
[8] Z.Geng and L.Haynes, Neural network solution for the forward
kinematics problem of a Stewart platform, Proc. Of the 1991 IEEE
Int'l Conf. on Robotics & Automation, California, April 1991, 2650-
2655.
[9] C.S.Yee and Kah-bin Lim, Forward kinematics solution of Stewart
platform using neural networks, Elsevier Science, Neurocomputing
16, 1997, 333-349.
[10] Nguyen, L., Patel, R.V. and Khorasani, K.: Neural Network
Architectures for the forward kinematics problem in robotics. In
Proc. of the Joint IEEE International Conference on Neural
Networks, San Diego, 1990, 393-399.
[11] D.Wang and A.Zilouchian, Solutions of kinematics of robot
manipulators using a kohonen self organizing neural network, Proc.
Of the 1997 IEEE Int'l Symp. on intelligent control, Turkey, July
1997, 251-255.
[12] L.H.Sang and M.C.Han, The Estimation for forward kinematic
solution of Stewart platform using the neural network, Proc. Of the
1999 IEEE/RSJ Int'l Conf. on Intelligent Robots & Systems, 1999,
501-506.
[13] Lee, S. and Kil, R.M.: Robot kinematic control based on
bidirectional mapping neural network. ," in Proc. IJCNN, San Diego,
CA, Vol. 3, 1990, 327-335.
[14] Ivakhnenko AG. Polynomial theory of complex systems. IEEE
Trans. Systems, Man, Cybernetics, 1971, SMC-1, 364-378.
[15] S.K. Oh, W. Pedrycz, B.J. Park, Polynomial neural networks
architecture: analysis & design, Information Sciences 141, 2002,
237-258.
[16] C.Y. Tsai, An iterative feature reduction algorithm for probabilistic
neural networks, the International Journal of Management Science,
Omega 28, 2000, 513-524.
[17] C.L. Philip chen and A.D. Mc Aulary, Robot kinematics Learning
computatons using polynomial neural networks, proceeding of the
1991 IEEE International conference on Robotics and Automation,
1991, 2638-2643.
[18] R. Boudreau, S. Darenfed, On the computation of the Direct
kinematics of parallel Maniputators using polynomial networks,
IEEE transactions on systems, man and cybernetics, Vol. 28, No. 2,
March 1998, 213-220.
[19] J.R. Jang, "ANFIS: Adaptive-network-based fuzzy inference
system," IEEE Transaction on systems, man and cybernetics, Vol.
23, No. 3, May/June 1993, 665-685.
@article{"International Journal of Information, Control and Computer Sciences:49850", author = "H. Sadjadian and H.D. Taghirad Member and A. Fatehi", title = "Neural Networks Approaches for Computing the Forward Kinematics of a Redundant Parallel Manipulator", abstract = "In this paper, different approaches to solve the
forward kinematics of a three DOF actuator redundant hydraulic
parallel manipulator are presented. On the contrary to series
manipulators, the forward kinematic map of parallel manipulators
involves highly coupled nonlinear equations, which are almost
impossible to solve analytically. The proposed methods are using
neural networks identification with different structures to solve the
problem. The accuracy of the results of each method is analyzed in
detail and the advantages and the disadvantages of them in
computing the forward kinematic map of the given mechanism is
discussed in detail. It is concluded that ANFIS presents the best
performance compared to MLP, RBF and PNN networks in this
particular application.", keywords = "Forward Kinematics, Neural Networks, Numerical
Solution, Parallel Manipulators.", volume = "2", number = "5", pages = "1342-8", }
