The explicit dynamic model and inertial parameters of the PUMA 560 arm

Abstract

A b s t r a c tTo provide COSMOS, a dynamic model baaed manipulator control system, with an improved dynamic model, a PUMA 560 arm waa diaaaaembled; the inertial propertiea of the individual links were meaaured; and an ezplicit model incorporating all ofthe non-zero meaaured parametera waa deriued. The ezplicit model of the PUMA arm has been obtained with a derivation procedure comprised of aeveral heuristic rulea for simplification. A aimplijied model, abbreviated from the full ezplicit model with a 1% aignijicance criterion, can be evaluated with 305 calculationa, one fifth the number required by the recuraive Newton-Euler method. The procedure used to derive the model ia laid out; the meaaured inertial parametera are preaented, and the model ia included in an appendiz. I n t r o d u c t i o nThe Implementation of dynamic control systems for manipulators has been hampered because the models are difficult to derive and computationally expensive, and because the needed parameters of the manipulator are generally unavailable. Recursive methods for computing the dynamic forces have been available for several years [Luh, Walker and Paul 1980a; Hollerbach 19801. Several authors have proposed and simulated the use of RNE in control systems [Luh, Walker and Paul 1980b; Kim and Shin 19851; and [Valavanis, Leahy and Sardsi 19851 have used the RNE to control a PUMA -600 arm. The RNE algorithm has also found use in the computation of forward dynamics for simulation [Walker and Orin 1982; Koozekanani et al. 19831, and nominal trajectory control [VukobratoviE and Kirfanski 19841. The RNE meets the need for calculation of dynamic forces in these applications, but does not offer several advantages available provided by an explicit model. The explicit model allows of the calculation decomposition based on a significance criterion or other criteria, and provides a more direct solution for dynamic simulation.The tremendous size of an explicit dynamic model is the greatest barrier to its realization. Correspondingly, a considerable portion of the effort spent investigating dynamic models for control has been directed toward efficient formulation and automatic generation of the manipulator equations of motion. Programs for automatic generation of manipulator dynamics are reported in [Likgeois et al. 1976;Megahed and Renaud 1982;Cesareo size of the models generated by these programs varies widely; and there is little consensus on the question of whether the explicit models can be made sufficiently compact to be used for control. Aldon and Likgeois [1984] present an algorithm for obtaining efficient dynamic models; but none-the-less recomend the use of recursive algorithms for real time control, claiming that the complete results are too complicated for real-time control of robots.As we show, explicit dynamic models of manipulators that are more computationally efficient than the alternative recursive algorithms can be obtained. The computational cost of the RNE algorithm, the full explicit PUMA model, and the explicit PWMA mo...

Iterative learning control with sampled-data feedback for robot manipulators

“…We assume the explicit dynamic model of PUMA560 robot arm (left-hand side of the Eq. (1)) with parameters reported by Armstrong et al [19], Corke, and Armstrong-Helouvry [20]. This first set of model parameters is described in Tab.…”

Dynamic External Force Feedback Loop Control of a Robot Manipulator Using a Neural Compensator—Application to the Trajectory Following in an Unknown Environment

“…The parameters are taken from the first three links of the PUMA 560 arm (Fig. 5) (Armstrong and Khatib, 1986) (it is supposed that its last three joints are blocked). Simulations carried out aim at evaluating the performances of our scheme for constrained tasks.…”

“…In Section 5, we present our neural approach applied to the control scheme. Section 6 shows simulation results for tasks carried out on two different environment types (planar and curved surface), by using a three-degrees-of-freedom industrial robot PUMA560 (Armstrong and Khatib, 1986), to demonstrate the robustness of the proposed scheme to payload uncertainties, position and environment stiffness, as well as dry and viscous frictions. Finally, conclusions are drawn in Section 7.…”

Video game device haptic interface for robotic arc welding

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“…If T D describes the desired homogeneous transform for the end of the robotic manipulator, equations for the candidate solutions for the angles of the last three joints can be found by careful selection of parameters in the following three matrix equations (see [18]): …”