Dynamic Parameter Identification of a 6 DOF Industrial Robot using Power Model

International audienceOff-line dynamic identification requires the use of a model linear in relation to the robot dynamic parameters and the use of linear least squares technique to calculate the parameters. Most of time, the used model is the Inverse Dynamic Identification Model (IDIM). However, the computation of its symbolic expressions is extremely tedious. In order to simplify the procedure, the use of the Power Identification Model (PIM), which is dramatically simpler to obtain and that contains exactly the same dynamic parameters as the IDIM, was previously proposed. However, even if the identification of the PIM parameters for a 2 degrees-of-freedom (DOF) planar serial robot was successful, its fails to work for 6 DOF industrial robots. This paper discloses the reasons of this failure and presents a methodology for the identification of the robot dynamic parameters using the PIM. The method is experimentally validated on an industrial 6 DOF Stäubli TX-40 robot

Global Identification of Joint Drive Gains and Dynamic Parameters of Parallel Robots

International audienceOff-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

Chapitre d'équation 1 Section 1

International audienceOff-line robot dynamic identification methods are mostly based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint force/torque that is linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In this paper it is proposed a new method for the identification of the total joint drive gains in one step using available joint sampled data given by the standard controller of the moving robot and using only the weighted mass of a payload, without any CAD values of its inertial parameters. A new inverse dynamic model calculates the current reference signal of each joint j that is linear in relation to the dynamic parameters of the robot, to the inertial parameters of a known mass fixed to the end-effector, and to the inverse of the joint j drive gain. This model is calculated with current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with the known mass fixed on the robot. Each joint j drive gain is calculated independently by the weighted LS solution of an over-determined linear systems obtained with the equations of the joint j. The method is experimentally validated on an industrial Stäubli RX-90 robot

Global Identification of Robot Drive Gains Parameters Using a Known Payload and Weighted Total Least Square Techniques

International audienceOff-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques 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). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In the previous works, it was proposed to identify each gain separately. This does not allow taking into account the dynamic coupling between the robot axes. In this paper the global joint drive gains parameters of all joints are calculated simultaneously. The method is based on the weighted total least squares solution of an over-determined linear system obtained with the inverse dynamic model calculated with available current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with a known payload fixed on the robot. The method is experimentally validated on an industrial 6 joint Stäubli TX-40 robot.

Global Identification of Drive Gains Parameters of Robots Using a Known Payload

International audienceOff-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques 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). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In the previous works, it was proposed to identify each gain separately. This does not allow taking into account the dynamic coupling between the robot axes. In this paper the global joint drive gains parameters of all joints are calculated simultaneously. The method is based on the total least squares solution of an over-determined linear system obtained with the inverse dynamic model calculated with available current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with a known payload fixed on the robot. The method is experimentally validated on an industrial Stäubli TX-40 robot

Global Identification of Drive Gains and Dynamic Parameters of Parallel Robots - Part 1: Theory

International audienceMost 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. Moreover the actuator drive gains are not calibrated which leads to identification errors. 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

New Method for Global Identification of the Joint Drive Gains of Robots using a Known Inertial Payload

International audienceOff-line robot dynamic identification methods are mostly based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint force/torque that is linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In this paper it is proposed a new method for the identification of the total joint drive gains in one step, using available joint sampled data given by the standard controller of the moving robot and using CAD or measured values of the inertial parameters of a known payload. A new inverse dynamic model calculates the current reference signal of each joint j that is linear in relation to the dynamic parameters of the robot, to the inertial parameters of a known payload fixed to the end-effector, and to the inverse of the joint j drive gain. This model is calculated with current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with the known payload fixed on the robot. Each joint j drive gain is calculated independently by the weighted LS solution of an over-determined linear systems obtained with the equations of the joint j. The method is experimentally validated on an industrial Stäubli RX-90 robot

Identification dynamique de robots avec un modèle de frottement sec fonction de la charge et de la vitesse

International audienceEn robotique, les pertes dans la chaine d'actionnement articulaire des robots sont généralement prises en compte dans le modèle dynamique par un effort de frottement visqueux proportionnel à la vitesse et par un effort constant de frottement sec. Pourtant, d'après la loi de Coulomb, le frottement sec de glissement varie avec les efforts de contact dans les éléments de transmission. Ainsi, cet effet est à prendre en compte pour les systèmes mécaniques soumis à de fortes variations de charge. Cet article présente un nouveau modèle dynamique dans lequel l'effort de frottement sec est proportionnel à la charge selon un coefficient dépendant de la vitesse. Une nouvelle procédure permet d'identifier ce modèle à partir de mesures faites sur le robot réalisant diverses trajectoires avec différents cas de charge. Une validation expérimentale est réalisée sur un robot industriel

Identification dynamique de robots avec un modèle de frottement sec fonction de la charge et de la vitesse

International audienceEn robotique, les pertes dans la chaine d'actionnement articulaire des robots sont généralement prises en compte dans le modèle dynamique par un effort de frottement visqueux proportionnel à la vitesse et par un effort constant de frottement sec. Pourtant, d'après la loi de Coulomb, le frottement sec de glissement varie avec les efforts de contact dans les éléments de transmission. Ainsi, cet effet est à prendre en compte pour les systèmes mécaniques soumis à de fortes variations de charge. Cet article présente un nouveau modèle dynamique dans lequel l'effort de frottement sec est proportionnel à la charge selon un coefficient dépendant de la vitesse. Une nouvelle procédure permet d'identifier ce modèle à partir de mesures faites sur le robot réalisant diverses trajectoires avec différents cas de charge. Une validation expérimentale est réalisée sur un robot industriel

Dynamic Parameter Identification of Actuation Redundant Parallel Robots: Application to the DualV

International audienceOff-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 - by 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). However, as actuation redundant parallel robots are over-constrained, their IDIM has infinity of solutions for the force/torque prediction, depending on the value of the desired overconstraint that is a priori unknown in the identification process. As a result, the IDIM cannot be used as it. This paper proposes a modified formulation for the IDIM of actuation redundant robots that can be used for identification purpose. This formulation consists of projecting the input torques/forces on the platform coordinates, thus leading to a unique solution of the model that can thus be used in the identification process. The identification of the inertial parameters of a planar parallel robot with actuation redundancy, the DualV, is then carried out using this modified IDIM. Experimental results show the validity of the method