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This paper presents a low-cost pose measuring device capable of simultaneously measuring all six coordinates (3 translations and 3 rotations) of a rigid body with respect to a given reference frame. The proposed system consists of a mechanical chain of rigid bodies and two encoders. The mechanism is a spatial four-bar linkage system with a symmetrical Revolute-Spherical-Spherical-Revolute (RSSR) kinematic structure, where two encoders measure the rotation of the revolute joints. The mechanism is investigated theoretically and solved kinematically using a numerical estimation method. The uncertainty of the pose determination, caused by the repeatability of the sensors, is estimated, as well as the achievable measurement range. A low uncertainty is achieved by a suitable design of the proposed kinematic chain. The mechanism is easy to realize with low tolerances and the correct definition of the length of the links allows a quite large workspace. The system can be profitably used in the calibration of robots or multi-axis machine tools where the actual pose of the gripper or spindle must be measured over the workspace of the machine. An experimental prototype is described, and the first experimental results are reported. • Six-coordinate low-cost pose measuring device. • Simple RSSR kinematic structure, easy realized with high accuracy and low backlash. • Great linear and angular accuracy of about 1 ⋅ 1 0 − 5 [m] and 1 ⋅ 10−4 [rad]. • Useful for kinematic calibration of robots or multi-axis machine. [ABSTRACT FROM AUTHOR]

Modeless industrial robot calibration plays an important role in the increasing employment of robots in industry. This approach allows to develop a procedure able to compensate the pose errors without complex parametric model. The paper presents a study aimed at comparing neural-kinematic (N-K) architectures for a modeless non-parametric robotic calibration. A multilayer perceptron feed-forward neural network, trained in a supervised manner with the back-propagation learning technique, is coupled in different modes with the ideal kinematic model of the robot. A comparative performance analysis of different neural-kinematic architectures was executed on a two degrees of freedom SCARA manipulator, for direct and inverse kinematics. Afterward the optimal schemes have been identified and further tested on a three degrees of freedom full SCARA robot and on a Stewart platform. The analysis on simulated data shows that the accuracy of the robot pose can be improved by an order of magnitude after compensation. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents the results of a research project whose aim is investigating, from both a theoretical and an experimental point of view, all the aspects connected to the optimal design and use of a 6 DoF draw-wire sensors based measuring system in the kinematic calibration of industrial robots context. One essential operation in calibration is the measurement of the pose of the robotic gripper in a predefined set of points inside the working space. For this purpose optical devices, like laser trackers, are usually employed due to their precision, although they are very expensive. Therefore, the study of a low-cost measuring system and the investigation of the reachable performances could represent a relevant outcome in the evolution of the calibration task. With this aim the design of a wire-sensors based measuring system was developed and applied to a six revolute degrees of freedom anthropomorphic robot. In a preliminary phase, with the aid of simulations tools, the measuring system was optimized to obtain isotropic accuracy and high sensitivity, while in the following experimental phase the same system was employed for the kinematic calibration of the robot, achieving an accuracy lower than the robot repeatability, which practically represents a physical limit. [Copyright &y& Elsevier]

In this paper, the matrix equation AX=XB used for hand to sensor calibration of robot-mounted sensors is analyzed using a geometrical approach. The analysis leads to an original way to describe the properties of the equation and to find all of its solutions. It will also be highlighted why, when multiple instances AiX=XBi (i=1,2,...) of the equation are to be solved simultaneously, the system is overconstrained. Finally, singular cases are also discussed. © 2005 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

This article presents and compares three algorithms for the geometric parameter identification of industrial robots to increase its accuracy (static calibration). The estimation is based on the measure of the gripper pose errors when the robot follows suitable trajectories. The algorithms are general and can be applied to any robot providing that its kinematics is known. After a theoretical introduction to the general methodologies, these are applied to a selective compliance assembly robot arm (SCARA) robot analyzing its performance (precision, efficiency). Experimental results obtained with three methodologies are presented and discussed. The measure of the gripper pose error is based on a laser triangulation technique whose working principles are also recalled. © 2000 John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time. [ABSTRACT FROM AUTHOR]