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

Calibration of 3-d.o.f. Translational Parallel Manipulators Using Leg Observations

The paper proposes a novel approach for the geometrical model calibration of quasi-isotropic parallel kinematic mechanisms of the Orthoglide family. It is based on the observations of the manipulator leg parallelism during motions between the specific test postures and employs a low-cost measuring system composed of standard comparator indicators attached to the universal magnetic stands. They are sequentially used for measuring the deviation of the relevant leg location while the manipulator moves the TCP along the Cartesian axes. Using the measured differences, the developed algorithm estimates the joint offsets and the leg lengths that are treated as the most essential parameters. Validity of the proposed calibration technique is confirmed by the experimental results.Comment: ISBN: 978-3-902613-20-

Calibration and Control of a Redundant Robotic Workcell for Milling Tasks

This article deals with the tuning of a complex robotic workcell of eight joints devoted to milling tasks. It consists of a KUKA (TM) manipulator mounted on a linear track and synchronised with a rotary table. Prior to any machining, the additional joints require an in situ calibration in an industrial environment. For this purpose, a novel planar calibration method is developed to estimate the external joint configuration parameters by means of a laser displacement sensor and avoiding direct contact with the pattern. Moreover, a redundancy resolution scheme on the joint rate level is integrated within a computer aided manufacturing system for the complete control of the workcell during the path tracking of a milling task. Finally, the whole system is tested in the prototyping of an orographic model.Andres De La Esperanza, FJ.; Gracia Calandin, LI.; Tornero Montserrat, J. (2011). Calibration and Control of a Redundant Robotic Workcell for Milling Tasks. International Journal of Computer Integrated Manufacturing. 24(6):561-573. doi:10.1080/0951192X.2011.566284S56157324

레이져 포인터를 이용한 Product-of-Exponentials 기반 직렬로봇 기구학적 보정 알고리즘

학위논문(석사)--서울대학교 대학원 :공과대학 기계항공공학부,2019. 8. 박종우.This thesis proposes a kinematic calibration algorithm for serial robots based on a minimal product of exponentials (POE) forward kinematic model. Generally, robot calibration requires the measurement of the end-effector frame (position and orientation), which typically requires special measurement equipment. To avoid using complex measurement devices and to make the calibration easy to implement for even the most general serial robots, in our approach we attach a laser pointer to the end-effector, which is then aimed at a set of fixed known reference points in the plane. Treating the laser as a prismatic joint and the reference point as the tip, kinematic calibration is then performed by minimizing the Cartesian position difference between the measured and estimated Cartesian tip position of the robot. Our method is validated via simulations and experiments involving a seven-dof industrial robot arm.위 논문은 Minimal POE (product of exponentials) 정기구학 모델에 기반한 직렬로봇 캘리브레이션 알고리즘을 제안한다. 일반적으로 로봇 캘리브레이션은 엔드이펙터 프레임의 위치와 방향을 측정하는 작업을 수행해야 하는데, 이는 특별한 측정장비를 필요로 한다. 복잡한 측정장비의 사용 회피와 다양한 형태의 직렬로봇에 쉽게 응용하기 위해, 이번 논문에서는 엔드이펙터에 레이저포인터를 부착하여 평면 위의 위치가 알려진 참조점들을 추적하여 캘리브레이션을 수행하는 방법을 제시한다. 캘리브레이션은 레이저포인터와 참조점을 각각 선형조인트와 팁으로 생각하여 로봇 팁 위치의 측정값과 추정값의 차이를 최소화하는 과정으로 진행된다. 7자유도 산업용 로봇 팔에 대해 시뮬레이션과 실제 공간에서의 실험을 통해 캘리브레이션 방식을 검증했다.1 Introduction 1 1.1 Existing Methods 2 1.2 Contributions of This Thesis 4 2 Kinematics Preliminaries 6 2.1 Geometric Background 6 2.1.1 The Lie Group Formulations 6 2.1.2 Screw Motions 8 2.1.3 Adjoint Representation 9 2.2 Forward Kinematics 9 2.2.1 The Product of Exponentials Formula 9 2.2.2 The Minimal Product of Exponentials Formula 11 2.3 Kinematic Error Model 14 2.3.1 Linearizing the Forward Kinematics 15 3 Calibration Methodology 19 3.1 The Concept of the Method 19 3.1.1 Forward Kinematics of a Robot With a Laser Pointer 19 3.1.2 The Error Model for Calibration 20 3.2 Calibration Algorithm 23 3.2.1 The Estimation Method of the Length of the Laser 24 3.2.2 Identification Process 25 4 Experiments 29 4.1 Simulation 1: 6-Dof Robot With Precise Data 29 4.2 Simulation 2: 6-Dof Robot With Noisy Data 31 4.3 Experiments on a 7-Dof Robot 34 5 Conclusion 39 A Appendix 41 A.1 Conversion From dq to dS and dSM [1] 41 Bibliography 43 Abstract 46Maste

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci

Amélioration de la précision d'un bras robotisé pour une application d'ébavurage

L'automatisation de procédés est une solution de plus en plus privilégiée pour réaliser des tâches complexes, ardues et même dangereuses pour l'humain. La flexibilité, le faible coût et le caractère compact des robots industriels en font des solutions très intéressantes. Bien que plusieurs développements aient permis de répondre en partie aux besoins de certaines industries, il reste que d'autres ont des contraintes importantes qui n'ont toujours pas été résolues. Par exemple, l'industrie de l'aéronautique exige de respecter des tolérances très serrées sur une grande variété de pièces, ce pourquoi les robots industriels n'ont pas été conçus. L'ébavurage robotisé est un exemple de procédé pour lequel la problématique d'imprécision des robots doit être résolue avant qu'ils ne puissent être utilisés en production. Ce mémoire propose donc d'explorer différentes possibilités pour arriver à réaliser 1' opération d'eôavurage selon les spécifications stipulées, avec des robots industriels. Des méthodes de calibration des dimensions du robot, faciles à mettre en oeuvre en milieux industriels, sont étudiées et comparées en simulation. La simulation et la mise en oeuvre d'une technique de calibration des dimensions de 1' outil sont faites pour en évaluer le potentiel. La technique offrant les meilleurs résultats est conservée pour démontrer la faisabilité du procédé. Finalement, l'environnement de mise en oeuvre de l'opération d'ébavurage robotisé est présenté. L'imprécision résiduelle du robot est en grande partie compensée par un capteur de force intégré au contrôleur du robot et une caméra. Plusieurs tests sont effectués et présentés pour démontrer le choix des paramètres utilisés pour réaliser 1' opération d' eôavurage. Les résultats sont présentés et démontrent la faisabilité du procédé d'ébavurage robotisé

Investigating deep-learning-based solutions for flexible and robust hand-eye calibration in robotics

The cameras are the main sensor for robots to perceive their environments because they provide high-quality information and their low-cost. However, transforming the information obtained from cameras into robotic actions can be challenging. To manipulate objects in camera scenes, robots need to establish a transformation between the camera and the robot base, which is known as hand-eye calibration. Achieving accurate hand-eye calibration is critical for precise robotic manipulation, yet traditional approaches can be time-consuming, error-prone, and fail to account for changes in the camera or robot base over time. This thesis proposes a novel approach that leverages the power of deep learning to automatically learn the mapping between the robot’s joint angles and the camera’s images, enabling real-time calibration updates. The approach samples the robot and camera spaces discretely and represents them continuously, enabling efficient and accurate computation of calibration parameters. By automating the calibration process and using deep learning algorithms, a more robust and efficient solution for hand-eye calibration in robotics is offered. To develop a robust and flexible hand-eye calibration approach, three main studies were conducted. In the first study, a deep learning-based regression architecture was developed that processes RGB and depth images, as well as the poses of a single reference point selected on the robot end-effector with respect to the robot base acquired through the robot kinematic chain. The success of this architecture was tested in a simulated environment and two real robotic environments, evaluating the metric error and precision. In the second approach, the success of the developed approach was evaluated by transferring from metric error to task error by performing a real robotic manipulation task, specifically a pick-and-place. Additionally, the performance of the developed approach was compared with a classic hand-eye calibration approach, using three evaluation criteria: real robotic manipulation task, computational complexity, and repeatability. Finally, the learned calibration space of the developed deep learning-based hand-eye calibration approach was extended with new observations over time using Continual learning, making the approach more robust and flexible in handling environmental changes. Two buffer-based approaches were developed to eliminate the catastrophic forgetting problem, which is forgetting learned information over time by considering new observations. The performance and comparison of these approaches with the training of the developed approach in the first study using all datasets from scratch were tested on a simulated and a real-world environment. Experimental results of this thesis reveal that: 1) a deep learning-based hand-eye calibration approach has competitive results with the classical approaches in terms of metric error (positional and rotational error deviation from the ground-truth) while eliminating data re-collection and re-training camera pose changes over time, and has 96 times better repeatability (precision) than the classic approach as well as it has the state-of-the-art result for it in comparison to the other deep learning-based hand-eye calibration approaches; 2) it also has competitive results with the classic approaches for performing a real-robotic manipulation task and reduces the computational complexity; 3) the leveraging deep-learning based hand-eye calibration approach with Continual Learning, it is possible to extend the learned calibration space over new observations without training the network from scratch with a lower accuracy gap (less than 1.5 mm and 2.5 degrees in the simulations and real-world environments for the translation and orientation components). Overall, the proposed approach offers a more efficient and robust solution for hand-eye calibration in robotics, providing greater accuracy and flexibility to adapt to environments where the poses of the robot and camera base change according to each other over time. These changes may come from either robot or camera movement. The results of the studies demonstrate the effectiveness of the approach in achieving precise and reliable robotic manipulation, making it a promising solution for robotics applications

Techniques For Sensor-Integrated Robotic Systems: Raman Spectra Analysis, Image Guidance, And Kinematic Calibration

Robotics and sensor technology have made impressive advancements over the years. There are now robotic systems that help perform surgeries or explore the surface of Mars, and there are sensors that detect trace amounts of explosives or identify diseased human tissue. The most powerful systems integrate robots and sensors, which are natural complements to each other. Sensors can provide information that might otherwise be unavailable due to indirect robotic manipulation (e.g., images of the target environment), and robots can provide suitably precise positioning of an analytical sensor. To have an effective sensor-integrated robotic system, multiple capabilities are needed in the areas of sensors, robotics, and techniques for robot/sensor integration. However, for many types of applications, there are shortcomings in the current technologies employed to provide these capabilities. For the analysis of complex sensor signals, there is a need for improved algorithms and open platforms that enable techniques to be shared. For the path planning and tracking of integrated sensors and the visualization of collected information, image guidance systems that support advanced analytical sensors would be very beneficial. For robotic placement of a sensor, easily usable calibration procedures and methods to overcome limited feedback could help improve the accuracy. To help address these issues, some novel systems and techniques were developed in this research. First, a software system was created to process, analyze, and classify data from a specific kind of sensor (a Raman spectrometer). The system is open and extensible, and it contains novel techniques for processing and analyzing the sensor data. Second, an image guidance system was made for use with a sensor-integrated robotic system (a Raman probe attached to a surgical system). The system supports tool tracking, sensor activation, real-time sensor data analysis, and presentation of the results in a 3D computer visualization of the environment. Third, a kinematic calibration technique was developed for serial manipulators. It requires no external measurement devices for calibration, provides solutions for some limitations of existing techniques, and can significantly enhance the positional accuracy of a robot to improve sensor placement. The implemented techniques and systems were successfully evaluated using various data sets and conditions. Together, the contributions of this work provide important building blocks for an accurate robot with an integrated analytical sensor. This type of a system would be a powerful tool for many future applications, such as a surgical robot that automatically scans for diseased tissue and assists the surgeon in the necessary treatment. Ultimately, this work is intended to foster the development of advanced sensor-integrated robotic systems