An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

This paper presents an overview of the literature on kinematic and calibration models of parallel mechanisms, the influence of sensors in the mechanism accuracy and parallel mechanisms used as sensors. The most relevant classifications to obtain and solve kinematic models and to identify geometric and non-geometric parameters in the calibration of parallel robots are discussed, examining the advantages and disadvantages of each method, presenting new trends and identifying unsolved problems. This overview tries to answer and show the solutions developed by the most up-to-date research to some of the most frequent questions that appear in the modelling of a parallel mechanism, such as how to measure, the number of sensors and necessary configurations, the type and influence of errors or the number of necessary parameters

Kinematic calibration of Orthoglide-type mechanisms from observation of parallel leg motions

The paper proposes a new calibration method for parallel manipulators that allows efficient identification of the joint offsets using observations of the manipulator leg parallelism with respect to the base surface. The method employs a simple and low-cost measuring system, which evaluates deviation of the leg location during motions that are assumed to preserve the leg parallelism for the nominal values of the manipulator parameters. Using the measured deviations, the developed algorithm estimates the joint offsets that are treated as the most essential parameters to be identified. The validity of the proposed calibration method and efficiency of the developed numerical algorithms are confirmed by experimental results. The sensitivity of the measurement methods and the calibration accuracy are also studied

Vision-based self-calibration and control of parallel kinematic mechanisms without proprioceptive sensing

International audienceThis work is a synthesis of our experience over parallel kinematic machine control, which aims at changing the standard conceptual approach to this problem. Indeed, since the task space, the state space and the measurement space can coincide in this class of mechanism, we came to redefine the complete modeling, identification and control methodology. Thus, it is shown in this paper that, generically and with the help of sensor-based control, this methodology does not require any joint measurement, thus opening a path to simplified mechanical design and reducing the number of kinematic parameters to identify. This novel approach was validated on the reference parallel kinematic mechanism (the Gough-Stewart platform) with vision as the exteroceptive sensor

Volumetric error compensation for industrial robots and machine tools

“A more efficient and increasingly popular volumetric error compensation method for machine tools is to compute compensation tables in axis space with tool tip volumetric measurements. However, machine tools have high-order geometric errors and some workspace is not reachable by measurement devices, the compensation method suffers a curve-fitting challenge, overfitting measurements in measured space and losing accuracy around and out of the measured space. Paper I presents a novel method that aims to uniformly interpolate and extrapolate the compensation tables throughout the entire workspace. By using a uniform constraint to bound the tool tip error slopes, an optimal model with consistent compensation capability is constructed. In addition to machine tools, industrial robots, are also becoming popularly used in manufacturing field. However, typical robot volumetric error compensation methods only consider constant errors such as link length and assembly errors while neglecting complicated kinematic errors such as strain wave gearing and out of rotating plane errors. Paper II presents a high-order joint-dependent model which describes both simple and complicated robot kinematic errors. A laser tracker with advantages of rapid data collection and a self-oriented position retroreflector are used for data collection. The experimental results show that nearly 20% of the robot kinematic errors are joint-dependent which are successfully captured by the proposed method. Paper III continues using the high-order joint-dependent robot error model while utilizing a new retroreflector with the ability of measuring robot position and orientation information simultaneously. More than 60% of measurement time is saved. Both position and orientation accuracy are also further improved”--Abstract, page iv

Visual Calibration, Identification and Control of 6-RSS Parallel Robots

Parallel robots present some outstanding advantages in high force-to-weight ratio, better stiffness and theoretical higher accuracy compared with serial manipulators. Hence parallel robots have been utilized increasingly in various applications. However, due to the manufacturing tolerances and defections in the robot structure, the positioning accuracy of parallel robots is basically equivalent with that of serial manipulators according to previous researches on the accuracy analysis of the Stewart Platform [1], which is difficult to meet the precision requirement of many potential applications. In addition, the existence of closed-chain mechanism yields difficulties in designing control system for practical applications, due to its highly coupled dynamics. Visual sensor is a good choice for providing non-contact measurement of the end-effector pose (position and orientation) with simplicity in operation and low cost compared to other measurement methods such as the coordinate measurement machine (CMM) [2] and the laser tracker [3]. In this research, a series of solutions including kinematic calibration, dynamic identification and visual servoing are proposed to improve the positioning and tracking performance of the parallel robot based on the visual sensor. The main contributions of this research include three parts. In the first part, a relative pose-based algorithm (RPBA) is proposed to solve the kinematic calibration problem of a six-revolute-spherical-spherical (6-RSS) parallel robot by using the optical CMM sensor. Based on the relative poses between the candidate and the initial configurations, a calibration algorithm is proposed to determine the optimal error parameters of the robot kinematic model and external parameters introduced by the optical sensor. The experimental results demonstrate that the proposal RPBA using optical CMM is an implementable and effective method for the parallel robot calibration. The second part focuses on the dynamic model identification of the 6-RSS parallel robots. A visual closed-loop output-error identification method based on an optical CMM sensor is proposed for the purpose of the advanced model-based visual servoing control design of parallel robots. By using an outer loop visual servoing controller to stabilize both the parallel robot and the simulated model, the visual closed-loop output-error identification method is developed and the model parameters are identified by using a nonlinear optimization technique. The effectiveness of the proposed identification algorithm is validated by experimental tests. In the last part, a dynamic sliding mode control (DSMC) scheme combined with the visual servoing method is proposed to improve the tracking performance of the 6-RSS parallel robot based on the optical CMM sensor. By employing a position-to-torque converter, the torque command generated by DSMC can be applied to the position controlled industrial robot. The stability of the proposed DSMC has been proved by using Lyapunov theorem. The real-time experiment tests on a 6-RSS parallel robot demonstrate that the developed DSMC scheme is robust to the modeling errors and uncertainties. Compared with the classical kinematic level controllers, the proposed DSMC exhibits the superiority in terms of tracking performance and robustness

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

Volumetric error compensation for 5-axis machine tools

This work presents a geometric error compensation method for large 5-axis machine tools. The compensation method presented here uses tool tip measurements recorded throughout the axis space to construct a position-dependent geometric error model that can easily be used for error compensation. The measurements are taken using a laser tracker, permitting rapid error data gathering at most locations in the axis space. First two model types are compared for generating table-based error compensation and experimental results are presented. Table-based compensation is then extended to machine tool controller types with restrictions on the number or combination of compensation tables using an artificial intelligence method. The overall methodology is then extended to the integration of additional instruments. A particular strength of the proposed methodology is the simultaneous generation of a complete set of compensation tables that accurately captures complicated kinematic errors independent of whether they arise from expected and unexpected sources --Abstract, page iv

Relative posture-based kinematic calibration of a 6-RSS parallel robot by optical coordinate measurement machine

In this article, a relative posture-based algorithm is proposed to solve the kinematic calibration problem of a 6-RSS parallel robot using the optical coordinate measurement machine system. In the research, the relative posture of robot is estimated using the detected pose with respect to the sensor frame through several reflectors which are fixed on the robot end-effector. Based on the relative posture, a calibration algorithm is proposed to determine the optimal error parameters of the robot kinematic model and external parameters introduced by the optical sensor. This method considers both the position and orientation variations and does not need the accurate location information of the detection sensor. The simulation results validate the superiority of the algorithm by comparing with the classic implicit calibration method. And the experimental results demonstrate that the proposal relative posture-based algorithm using optical coordinate measurement machine is an implementable and effective method for the parallel robot calibration