Optimized Dynamic Calibration of a Scara Robot

Indri, Marina; Calafiore, Giuseppe Carlo; Legnani, Giovanni; Jatta, F.; Visioli, Antonio

doi:10.3182/20020721-6-es-1901.00884

Cited by 15 publications

(10 citation statements)

References 11 publications

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“…In addition, other N f coefficients of the friction model yield the compound parameters set π. The selected friction model [22] provides the j-th joint friction torque function of three parameters,…”

Section: A Dynamics Modeling and Estimationmentioning

confidence: 99%

Robot-dynamic calibration improvement by local identification

Pedrocchi

Villagrossi

Vicentini

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Notwithstanding the research on dynamic modelling of Industrial Robots (IRs hereafter) covers the last three decades, improvements are necessary to enable IRs adoption in technological tasks where high dynamics or interaction with environment is needed, e.g. deburring, milling, laser cutting etc. Indeed, this class of applications displays even more the necessity of high-accuracy tracking especially in workspace sub-regions, while common IR dynamic calibration methods often span the workspace at large (in term of positions and high velocities) resulting in an averagely fitting models. Open issues are therefore on the applicability/scalability of standard methods in workspace sub-regions and on the metrics used for the calibration performance evaluation. The paper proposes an algorithm designed to high-accuracy local dynamic identification, comparing it with the results achievable by a common IRs dynamic calibration method and by the same method scaled to a workspace sub-region. In addition, unlike from standard, the here reported experimental comparison is made by evaluating the torque prediction error for IRs robot moving along path programmed by standard/commercial IR motion planner and not along path belonging to the same template-class of trajectory used in identification phase.

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Section: A Dynamics Modeling and Estimationmentioning

confidence: 99%

Robot-dynamic calibration improvement by local identification

Pedrocchi

Villagrossi

Vicentini

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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“…Other identification methods have been tried: the Total Least-Squares (Xi, 1995); the extended Kalman filter (Gautier & Poignet, 2001;Kostic et al, 2004); an algorithm based on Linear Matrix Inequality (LMI) tools (Indri et al, 2002); a Maximum Likelihood (ML) approach (Olsen, Swevers, & Verdonck, 2002); the Closed-Loop Output-Error method (Östring, Gunnarsson, &Norrlöf, 2003;Gautier, Janot, & Vandanjon, 2013); the Set Membership Uncertainty method (Ramdani & Poignet, 2005); a method which estimates the nonlinear effects in the frequency domain (Wernholt & Gunnarsson, 2008); and an instrumental variable approach that combines the direct and inverse dynamic models (Janot, Vandanjon, & Gautier, 2014a;Janot, Vandanjon, & Gautier, 2014b).…”

Section: Robot Identificationmentioning

confidence: 99%

Identification and control of electro-mechanical systems using state-dependent parameter estimation

Janot¹,

Young

Gautier

2016

International Journal of Control

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International audienceThis paper addresses the important topic of electro-mechanical systems identification with an application in robotics. The standard inverse dynamic identification model with least squares (IDIM-LS) method of identifying models for robotic systems is based on the use of a continuous-time inverse dynamic model whose parameters are identified from experimental data by linear LS estimation. The paper describes a new alternative but related approach that exploits the state-dependent parameter (SDP) method of nonlinear model estimation and compares its performance with that of IDIM-LS. The SDP method is a two-stage identification procedure able to identify the presence and graphical shape of nonlinearities in dynamic system models with a minimum of a priori assumptions. The performance of the SDP method is evaluated on two electro-mechanical systems: the electro-mechanical positioning system and the second link of the TX40 robot. The experimental results demonstrate how SDP identification helps to avoid over-reliance on prior conceptions about the nature of the nonlinear characteristics and correct any deficiencies in this regard. Finally, a simulation study shows how the resulting SDP model is able to facilitate nonlinear control system design using linear-like design procedures

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“…The minimal size N π of the base set π 0 is demonstrated [11] to be 40 for a 6-dof anthropomorphic manipulator, in addition of which other N f coefficients of the friction model yield the compound parameters set π. The selected friction model [20] provides the j-th joint friction torque in the form:…”

Section: A Dynamics Modeling and Estimationmentioning

confidence: 99%

Optimal robot dynamics local identification using genetic-based path planning in workspace subregions

Villagrossi¹,

Pedrocchi²,

Vicentini³

et al. 2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Methods for dynamic calibrations of Industrial Robots (IR) are increasing their importance in many applications because of high performances attained by model-based control strategies. Most of known state-of-the-art methods aim at modeling robots along the complete workspace, often affecting the identified parameters with loss of physical meaning (e.g. negative inertia values) and requiring a wide exploration of the workspace both in term of joint positions and velocities (accelerations). Actually, many IR tasks require dynamic accuracy in limited portion of the workspace and commonly display mild dynamics. Local identification of dynamics parameters in task conditions could therefore increase the predictive capability of the model for that operation. This work proposes the use of a parametric-description of trajectories in Cartesian space, corresponding to the standard industrial path-description as a series of via-points in most of programming languages. The identification of the optimal exciting Cartesian trajectory in a local sub-region of the workspace is made by a genetic algorithm over the template trajectory description. The use of an IR real interpolator allows to match computational and task execution conditions.

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Optimized Dynamic Calibration of a Scara Robot

Cited by 15 publications

References 11 publications

Robot-dynamic calibration improvement by local identification

Robot-dynamic calibration improvement by local identification

Identification and control of electro-mechanical systems using state-dependent parameter estimation

Optimal robot dynamics local identification using genetic-based path planning in workspace subregions

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