Uncertainty Modelling of High-precision Trajectories for Industrial Real-time Measurement Applications

Within the field of large volume metrology, kinematic tasks such as the movement of an industrial robot have been measured using laser trackers. In spite of the kinematic applications, to date most research has focused on static measurements. It is crucial to have a reliable uncertainty of kinematic measurements in order to assess spatiotemporal path deviations of a robot. With this in mind an approach capable of real-time was developed, to determine the uncertainties of kinematic measurements

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

A method for the assessment and compensation of positioning errors in industrial robots

Industrial Robots (IR) are currently employed in several production areas as they enable flexible automation and high productivity on a wide range of operations. The IR low positioning performance, however, has limited their use in high precision applications, namely where positioning errors assume importance for the process and directly affect the quality of the final products. Common approaches to increase the IR accuracy rely on empirical relations which are valid for a single IR model. Also, existing works show no uniformity regarding the experimental procedures followed during the IR performance assessment and identification phases. With the aim to overcome these restrictions and further extend the IR usability, this paper presents a general method for the evaluation of IR pose and path accuracy, primarily focusing on instrumentation and testing procedures. After a detailed description of the experimental campaign carried out on a KUKA KR210 R2700 Prime robot under different operating conditions (speed, payload and temperature state), a novel online compensation approach is presented and validated. The position corrections are processed with an industrial PC by means of a purposely developed application which receives as input the position feedback from a laser tracker. Experiments conducted on straight paths confirmed the validity of the proposed approach, which allows remarkable reductions (in the order of 90%) of the orthogonal deviations and in-line errors during the robot movements

Multi-scale metrology for automated non-destructive testing systems

This thesis was previously held under moratorium from 5/05/2020 to 5/05/2022The use of lightweight composite structures in the aerospace industry is now commonplace. Unlike conventional materials, these parts can be moulded into complex aerodynamic shapes, which are diffcult to inspect rapidly using conventional Non-Destructive Testing (NDT) techniques. Industrial robots provide a means of automating the inspection process due to their high dexterity and improved path planning methods. This thesis concerns using industrial robots as a method for assessing the quality of components with complex geometries. The focus of the investigations in this thesis is on improving the overall system performance through the use of concepts from the field of metrology, specifically calibration and traceability. The use of computer vision is investigated as a way to increase automation levels by identifying a component's type and approximate position through comparison with CAD models. The challenges identified through this research include developing novel calibration techniques for optimising sensor integration, verifying system performance using laser trackers, and improving automation levels through optical sensing. The developed calibration techniques are evaluated experimentally using standard reference samples. A 70% increase in absolute accuracy was achieved in comparison to manual calibration techniques. Inspections were improved as verified by a 30% improvement in ultrasonic signal response. A new approach to automatically identify and estimate the pose of a component was developed specifically for automated NDT applications. The method uses 2D and 3D camera measurements along with CAD models to extract and match shape information. It was found that optical large volume measurements could provide suffciently high accuracy measurements to allow ultrasonic alignment methods to work, establishing a multi-scale metrology approach to increasing automation levels. A classification framework based on shape outlines extracted from images was shown to provide over 88% accuracy on a limited number of samples.The use of lightweight composite structures in the aerospace industry is now commonplace. Unlike conventional materials, these parts can be moulded into complex aerodynamic shapes, which are diffcult to inspect rapidly using conventional Non-Destructive Testing (NDT) techniques. Industrial robots provide a means of automating the inspection process due to their high dexterity and improved path planning methods. This thesis concerns using industrial robots as a method for assessing the quality of components with complex geometries. The focus of the investigations in this thesis is on improving the overall system performance through the use of concepts from the field of metrology, specifically calibration and traceability. The use of computer vision is investigated as a way to increase automation levels by identifying a component's type and approximate position through comparison with CAD models. The challenges identified through this research include developing novel calibration techniques for optimising sensor integration, verifying system performance using laser trackers, and improving automation levels through optical sensing. The developed calibration techniques are evaluated experimentally using standard reference samples. A 70% increase in absolute accuracy was achieved in comparison to manual calibration techniques. Inspections were improved as verified by a 30% improvement in ultrasonic signal response. A new approach to automatically identify and estimate the pose of a component was developed specifically for automated NDT applications. The method uses 2D and 3D camera measurements along with CAD models to extract and match shape information. It was found that optical large volume measurements could provide suffciently high accuracy measurements to allow ultrasonic alignment methods to work, establishing a multi-scale metrology approach to increasing automation levels. A classification framework based on shape outlines extracted from images was shown to provide over 88% accuracy on a limited number of samples

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.Comment: 25 pages, Technical report, related to Burke and Lasenby, AMDO 2014 conference paper. Code sample: https://github.com/mgb45/SignerBodyPose Video: https://www.youtube.com/watch?v=dJMTSo7-uF

Incorporation of the influences of kinematics parameters and joints tilting for the calibration of serial robotic manipulators

Serial robotic manipulators are calibrated to improve and restore their accuracy and repeatability. Kinematics parameters calibration of a robot reduces difference between the model of a robot in the controller and its actual mechanism to improve accuracy. Kinematics parameter’s error identification in the standard kinematics calibration has been configuration independent which does not consider the influence of kinematics parameter on robot tool pose accuracy for a given configuration. This research analyses the configuration dependent influences of kinematics parameters error on pose accuracy of a robot. Based on the effect of kinematics parameters, errors in the kinematics parameters are identified. Another issue is that current kinematics calibration models do not incorporate the joints tilting as a result of joint clearance, backlash, and flexibility, which is critical to the accuracy of serial robotic manipulators, and therefore compromises a pose accuracy. To address this issue which has not been carefully considered in the literature, this research suggested an approach to model configuration dependent joint tilting and presents a novel approach to encapsulate them in the calibration of serial robotic manipulators. The joint tilting along with the kinematics errors are identified and compensated in the kinematics model of the robot. Both conventional and proposed calibration approach are tested experimentally, and the calibration results are investigated to demonstrate the effectiveness of this research. Finally, the improvement in the trajectory tracking accuracy of the robot has been validated with the help of proposed low-cost measurement set-up.Thesis (M.Phil.) (Research by Publication) -- University of Adelaide, School of Mechanical Engineering , 201

Preintegrated Velocity Bias Estimation to Overcome Contact Nonlinearities in Legged Robot Odometry

In this paper, we present a novel factor graph formulation to estimate the pose and velocity of a quadruped robot on slippery and deformable terrain. The factor graph introduces a preintegrated velocity factor that incorporates velocity inputs from leg odometry and also estimates related biases. From our experimentation we have seen that it is difficult to model uncertainties at the contact point such as slip or deforming terrain, as well as leg flexibility. To accommodate for these effects and to minimize leg odometry drift, we extend the robot's state vector with a bias term for this preintegrated velocity factor. The bias term can be accurately estimated thanks to the tight fusion of the preintegrated velocity factor with stereo vision and IMU factors, without which it would be unobservable. The system has been validated on several scenarios that involve dynamic motions of the ANYmal robot on loose rocks, slopes and muddy ground. We demonstrate a 26% improvement of relative pose error compared to our previous work and 52% compared to a state-of-the-art proprioceptive state estimator.Comment: Accepted to ICRA 2020. Video: youtu.be/w1Sx6dIqgQ

Traceable onboard metrology for machine tools and large-scale systems

Esta tesis doctoral persigue la mejora de las funcionalidades de las máquinas herramienta para la fabricación de componentes de alto valor añadido. En concreto, la tesis se centra en mejorar la precisión de las máquinas herramienta en todo su volumen de trabajo y en desarrollar el conocimiento para realizar la medición por coordenadas trazable con este medio productivo. En realidad, la tecnología para realizar mediciones en máquina herramienta ya está disponible, como son los palpadores de contacto y los softwares de medición, sin embargo, hay varios factores que limitan la trazabilidad de la medición realizada en condiciones de taller, que no permiten emplear estas medidas para controlar el proceso de fabricación o validar la pieza en la propia máquina-herramienta, asegurando un proceso de fabricación de cero-defectos. Aquí, se propone el empleo del documento técnico ISO 15530-3 para piezas de tamaño medio. Para las piezas de gran tamaño se presenta una nueva metodología basada en la guía VDI 2617-11, que no está limitada por el empleo de una pieza patrón para caracterizar el error sistemático de la medición por coordenadas en la máquina-herramienta. De esta forma, se propone una calibración previa de la máquina-herramienta mediante una solución de multilateración integrada en máquina, que se traduce en la automatización del proceso de verificación y permite reducir el tiempo y la incertidumbre de medida. En paralelo, con el conocimiento generado en la integración de esta solución en la máquina-herramienta, se propone un nuevo procedimiento para la caracterización de la precisión de apunte del telescopio LSST en todo su rango de trabajo. Este nuevo procedimiento presenta una solución automática e integrada con tecnología láser tracker para aplicaciones de gran tamaño donde la precisión del sistema es un requerimiento clave para su buen funcionamiento.<br /

Thermal Performance of a Multi-Axis Smoothing Cell

Multi Axis Robots have traditionally been used in industry for pick and place, de-burring, and welding operations. Increasing technological advances have broadened their application and today robots are increasingly being used for higher precision applications in the medical and nuclear sectors. In order to use robots in such roles it is important to understand their performance. Thermal effects in machine tools are acknowledged to account for up to 70% of all errors (Bryan J. , 1990) and therefore need to be considered. This research investigates thermal influences on the accuracy and repeatability of a six degree of freedom robotic arm, which forms an integral part of a smoothing cell. The cell forms part of a process chain currently being developed for the processing of high accuracy freeform surfaces, intended for use on the next generation of ground based telescopes. The robot studied was a FANUC 710i/50 with a lapping spindle the end effector. The robot geometric motions were characterised and the structure was thermally mapped at the latter velocity. The thermal mapping identified the key areas of the robot structure requiring more detailed analysis. Further investigation looked into thermal variations in conjunction with geometric measurements in order to characterise the robot thermal performance. Results showed thermal variations of up to 13ºC over a period of six hours, these produced errors of up to 100μm over the 1300mm working stroke slow. Thermal modelling carried out predicted geometric variation of 70μm to 122μm for thermal variations up to 13ºC over a period of six hours. The modelling was 50% to 75% efficient in predicting thermal error magnitudes in the X axis. With the geometric and modelling data a recommendation for offline compensation would enable significant improvement in the robots positioning capability to be achieved

Modeling and Control of Flexible Link Manipulators

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio