In this article, we review the dynamic control of parallel kinematic machines. It is shown that the classical control strategies from serial robotics generally used for parallel kinematic machine have to be rethought. Indeed, it is first shown that the joint space control is not relevant for these mechanisms for several reasons such as mechanical behavior or computational efficiency. Consequently, Cartesian space control should be preferred over joint space control. Nevertheless, some modifications to the well-known Cartesian space control strategies of serial robotics are proposed to make them perfectly suited to parallel kinematic machines, particularly a solution using an exteroceptive measure of the end-effector pose. The expected improvement in terms of accuracy, stability and robustness are discussed. A comparison between the main presented strategies is finally performed both in simulation and experiments.

A Review on the Dynamic Control of Parallel Kinematic Machines: Theory and Experiments

The paper deals with geometric calibration of industrial robots and focuses on reduction of the measurement noise impact by means of proper selection of the manipulator configurations in calibration experiments. Particular attention is paid to the enhancement of measurement and optimization techniques employed in geometric parameter identification. The developed method implements a complete and irreducible geometric model for serial manipulator, which takes into account different sources of errors (link lengths, joint offsets, etc). In contrast to other works, a new industry-oriented performance measure is proposed for optimal measurement configuration selection that improves the existing techniques via using the direct measurement data only. This new approach is aimed at finding the calibration configurations that ensure the best robot positioning accuracy after geometric error compensation. Experimental study of heavy industrial robot KUKA KR-270 illustrates the benefits of the developed pose strategy technique and the corresponding accuracy improvement. Geometric calibration of industrial robotsReduction of the measurement noise impact by means of proper selection of the manipulator configurations in calibration experimentsA new industry-oriented performance measure for optimal measurement configuration selectionExperimental study of heavy industrial robot KUKA KR-270

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Geometric calibration of industrial robots using enhanced partial pose measurements and design of experiments

https://hal-mines-nantes.archives-ouvertes.fr/hal-01201696/document

Identification of the manipulator stiffness model parameters in industrial environment

Unlike the traditional robot calibration methods, which need external expensive calibration apparatus and elaborate setups to measure the 3D feature points in the reference frame, a vision-based self-calibration method for a serial robot manipulator, which only requires a ground-truth scale in the reference frame, is proposed in this paper. The proposed algorithm assumes that the camera is rigidly attached to the robot end-effector, which makes it possible to obtain the pose of the manipulator with the pose of the camera. By designing a manipulator movement trajectory, the camera poses can be estimated up to a scale factor at each configuration with the factorization method, where a nonlinear least-square algorithm is applied to improve its robustness. An efficient approach is proposed to estimate this scale factor. The great advantage of this self-calibration method is that only image sequences of a calibration object and a ground-truth length are needed, which makes the robot calibration procedure more autonomous in a dynamic manufacturing environment. Simulations and experimental studies on a PUMA 560 robot reveal the convenience and effectiveness of the proposed robot self-calibration approach.

Autonomous robot calibration using vision technology

Presents a numerical method for the determination of the identifiable parameters of parallel robots. The special case of Stewart-Gough 6 degrees-of-freedom parallel robots is studied for classical and self calibration methods, but this method can be generalized to any kind of parallel robot. The method is based on QR decomposition of the observation matrix of the calibration system. Numerical relations between the parameters which are identified and those which are not identifiable can be obtained for each method.

/pdf/identifiable-parameters-for-parallel-robots-kinematic-4w1kfjz5tx.pdf

Identifiable parameters for parallel robots kinematic calibration

Presents a method for the autonomous calibration of six degrees-of-freedom parallel robots. The calibration makes use of the motorized prismatic joint positions corresponding to some sets of configurations where in each set either a passive universal joint or a passive spherical joint is fixed using a lock mechanism. Simulations give us an idea about the number of sets that must be used, the number of configurations by set and the effect of noise on the calibration accuracy. The main advantage of this method is that it can be executed rapidly without need to external sensors to measure the position or the orientation of the mobile platform.

Self calibration of Stewart-Gough parallel robots without extra sensors

Presents a method for the kinematic calibration of six degrees of freedom parallel robots using two inclinometers. The calibration model takes into account the error on the angle between the inclinometers axes. The estimation of the parameters is carried out using the Levenberg-Marquardt algorithm. The number of configurations needed and the effect of noise on sensors data are studied using simulations.

S. Besnard

Papers

Self calibration of Stewart-Gough parallel robots without extra sensors

Calibration of parallel robots using two inclinometers