×

Global identification of joint drive gains and dynamic parameters of parallel robots. (English) Zbl 1391.70016

Summary: Off-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal – the input reference of the motor current loop – with the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). Most of the papers dealing with the dynamic parameters identification of parallel robots are based on simple models, which take only the dynamics of the moving platform into account. However, for advanced applications such as output force control, in which the robot interaction force with the environment are estimated from the values of the input reference, both identifications of the full robot model and joint drive gains are required to obtain the best results. In this paper, a systematic way to derive the full dynamic identification model of parallel robots is proposed in combination with a method that allows the identification of both robot inertial parameters and drive gains. The method is based on the total least squares solution of an over-determined linear system obtained with the inverse dynamic model. This model is calculated with available input reference of the motor current loop and joint position sampled data while the robot is tracking some reference trajectories without load on the robot and some trajectories with a known payload fixed on the robot. The method is experimentally validated on a prototype of parallel robot, the Orthoglide.

MSC:

70E60 Robot dynamics and control of rigid bodies
93C85 Automated systems (robots, etc.) in control theory

Software:

VanHuffel

References:

[1] Merlet, J.P.: Parallel Robots, 2nd edn. Springer, Berlin (2006) · Zbl 1110.70002
[2] Amiral, Y., Francois, G.F., Pontnauand, J., Dafaoui, M.: Design and control of a new six-dof parallel robot: application to equestrian gait simulation. Mechatronics 6, 227-239 (1996) · doi:10.1016/0957-4158(95)00068-2
[3] Vivas, A., Poignet, P.: Predictive functional control of a parallel robot. Control Eng. Pract. 13, 863-874 (2005) · Zbl 1429.62195 · doi:10.1016/j.conengprac.2004.10.001
[4] Khalil, W., Dombre, E.: Modeling, Identification and Control of Robots. Hermes Penton, London (2002) · Zbl 1023.70001
[5] Khalil, W.; Gautier, M.; Lemoine, P., Identification of the payload inertial parameters of industrial manipulators, Roma, Italy, April 2007
[6] Restrepo, P. P.; Gautier, M., Calibration of drive chain of robot joints, 526-531 (1995) · doi:10.1109/CCA.1995.555778
[7] Corke, P.: In situ measurement of robot motor electrical constants. Robotica 23(14), 433-436 (1996) · doi:10.1017/S0263574700019834
[8] Gautier, M.; Briot, S., New method for global identification of the joint drive gains of robots using a known inertial payload, Orlando, Florida, USA, December 2011
[9] Gautier, M.; Briot, S., New method for global identification of the joint drive gains of robots using a known payload mass, San Francisco, CA, USA, September
[10] Vivas, A.; Poignet, P.; Marquet, F.; Pierrot, F.; Gautier, M., Experimental dynamic identification of a fully parallel robot, Taipei, Taiwan
[11] Guégan, S.; Khalil, W.; Lemoine, P., Identification of the dynamic parameters of the orthoglide, Taipei, Taiwan, September
[12] Renaud, P., Vivas, A., Andreff, N., Poignet, P., Martinet, P., Pierrot, F., Company, O.: Kinematic and dynamic identification of parallel mechanisms. Control Eng. Pract. 14, 1099-1109 (2006) · doi:10.1016/j.conengprac.2005.06.011
[13] Grotjahn, M., Heiman, B., Abdellatif, H.: Identification of friction and rigid-body dynamics of parallel kinematic structures for model-based control. Multibody Syst. Dyn. 11, 273-294 (2004) · Zbl 1143.70360 · doi:10.1023/B:MUBO.0000029426.05860.c2
[14] Diaz-Rodriguez, M., Mata, V., Valera, A., Page, A.: A methodology for dynamic parameters identification of 3-dof parallel robots in terms of relevant parameters. Mech. Mach. Theory 45, 1337-1356 (2010) · Zbl 1359.70014 · doi:10.1016/j.mechmachtheory.2010.04.007
[15] Chablat, D., Wenger, P.: Architecture optimization of a 3-dof parallel mechanism for machining applications, the Orthoglide. IEEE Trans. Robot. Autom. 19(3), 403-410 (2003) · doi:10.1109/TRA.2003.810242
[16] Briot, S.; Gautier, M., Global identification of drive gains and dynamic parameters of parallel robots - Part 1: Theory (2012)
[17] Briot, S.; Gautier, M., Global identification of drive gains and dynamic parameters of parallel robots - Part 2: Case study (2012)
[18] Ibrahim, O., Khalil, W.: Inverse and direct dynamic models of hybrid robots. Mech. Mach. Theory 45, 627-640 (2010) · Zbl 1254.70010 · doi:10.1016/j.mechmachtheory.2009.11.007
[19] Pfurner, M.; Husty, M. L., Implementation of a new and efficient algorithm for the inverse kinematics of serial 6R chains, 91-98 (2010), Berlin · doi:10.1007/978-90-481-9689-0_11
[20] Briot, S., Arakelian, V.: Optimal force generation of parallel manipulators for passing through the singular positions. Int. J. Robot. Res. 27(8), 967-983 (2008) · doi:10.1177/0278364908094403
[21] Nenchev, D.N., Bhattacharya, S., Uchiyama, M.: Dynamic analysis of parallel manipulators under the singularity-consistent parameterization. Robotica 15(4), 375-384 (1997) · doi:10.1017/S0263574797000465
[22] Gautier, M., Dynamic identification of robots with power model, Albuquerque, USA, April
[23] Gautier, M.: Numerical calculation of the base inertial parameters. J. Robot. Syst. 8(4), 485-506 (1991) · Zbl 0727.70006 · doi:10.1002/rob.4620080405
[24] Gautier, M., Khalil, W.: Exciting trajectories for the identification of the inertial parameters of robots. Int. J. Robot. Res. 11(4), 362-375 (1992) · doi:10.1177/027836499201100408
[25] Swevers, J., Ganseman, C., Tukel, D., DeSchutter, J., VanBrussel, H.: Optimal robot excitation and identification. IEEE Trans. Robot. Autom. 13, 730-740 (1997) · doi:10.1109/70.631234
[26] Khalil, W., Ibrahim, O.: General solution for the dynamic modeling of parallel robots. J. Intell. Robot. Syst. 49(1), 19-37 (2007) · doi:10.1007/s10846-007-9137-x
[27] Van Huffel, S., Vandewalle, J.: The Total Least Squares Problem: Computational Aspects and Analysis. Frontiers in Applied Mathematics Series, vol. 9. SIAM, Philadelphia (1991) · Zbl 0789.62054 · doi:10.1137/1.9781611971002
[28] Gautier, M.; Vandanjon, P.; Presse, C., Identification of inertial and drive gain parameters of robots, Lake Buena, Vista, FL, USA
[29] Golub, G.H., Van Loan, C.F.: Matrix Computation, 2nd edn. J. Hopkins, Baltimore (2006)
[30] Gautier, M.; Briot, S., Global identification of drive gains parameters of robots using a known payload (2012)
[31] Moon, F.C.: Applied Dynamics. Wiley, New York (2007)
[32] Gautier, M.; Briot, S., Global identification of drive gains parameters of robots using a known payload, Saint Paul, Minesota, USA, May 14-18 · doi:10.1109/ICRA.2012.6225099
[33] Jubien, A.; Gautier, M., Global identification of spring balancer, dynamic parameters and drive gains of heavy industrial robots, Tokyo, Japan, November 3-7 · doi:10.1109/IROS.2013.6696525
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.