Design of Experiments for Calibration of Planar Anthropomorphic Manipulators

The paper presents a novel technique for the design of optimal calibration experiments for a planar anthropomorphic manipulator with n degrees of freedom. Proposed approach for selection of manipulator configurations allows essentially improving calibration accuracy and reducing parameter identification errors. The results are illustrated by application examples that deal with typical anthropomorphic manipulators.Comment: Advanced Intelligent Mechatronics (AIM), 2011 IEEE/ASME International Conference on, Budapest : Hungary (2011

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

Design and validation of a system for controlling a robot for 3D ultrasound scanning of the lower limbs

Peripheral arterial disease (PAD) is a common circulatory problem featured by arterial narrowing or stenosis, usually in the lower limbs (i.e. legs). Without sufficient blood supply, in the case of PAD, the patient may suffer from intermittent claudication, or even require an amputation. Due to the PAD’s high prevalence yet low public awareness in the early stages, its diagnosis becomes very important. Among the most common medical imaging technologies in PAD diagnosis, the ultrasound probe has the advantages of lower cost and non-radiation. Traditional ultrasound scanning is conducted by sonographers and it causes musculoskeletal disorders in the operators. In addition, the data obtained from the manual operation are unable for the three-dimensional reconstruction of the artery needed for further study. Medical ultrasound robots release sonographers from routine lifting strain and provide accurate data for three-dimensional reconstruction. However, most existing medical ultrasound robots are designed for other purposes, and are unsuited to PAD diagnosis in the lower limbs. In this study, we present a novel medical ultrasound robot designed for PAD diagnosis in the lower limbs. The robot platform and the system setup are illustrated. Its forward and inverse kinematic models are solved by decomposing a complex parallel robot into several simple assemblies. Singularity issues and workspace are also discussed. Robots need to meet certain accuracy requirements to perform dedicated tasks. Our robot is calibrated by direct measurement with a laser tracker. The calibration method used is easy to implement without requiring knowledge of advanced calibration or heavy computation. The calibration result shows that, as an early prototype, the robot has noticeable errors in manufacturing and assembling. The implemented calibration method greatly improves the robot's accuracy. A force control design is essential when the robot needs to interact with an object/environment. Variable admittance controllers are implemented to adapt the variable stiffness encountered in human-robot interaction. An intuitive implementation of the passivity theory is proposed to ensure that the admittance model possesses a passivity property. Finally, experiments involving human interaction demonstrate the effectiveness of the proposed control design

Robot Calibration Using Artificial Neural Networks

Robot calibration is an integrated procedure of measurement and data processing to improve and maintain robot positioning accuracy. Existing robot calibration techniques require extensive human intervention and off-line processing, which preclude the techniques from being used to perform on-site calibration in an industrial environment at regular intervals. This thesis investigates and develops intelligent calibration processing algorithms and a novel measurement method toward rapid autonomous robot calibration in a shop-floor environment.Artificial Neural Network (ANN) techniques have been vigorously investigated for calibration data processing (modelling, identification and compensation). A new identification algorithm has been developed for estimating robot kinematic parameter errors using Hopfield continuous-valued type Recurrent Neural Network (RNN). The RNN-based algorithm is computationally more efficient and robust compared with conventional optimisation approaches.A generic accuracy model which accounts for various error sources was introduced. A higher-order neural network was used for implementation of the generic accuracy model. Due to the ANN learning capability, computational power and adaptability, the ANN-based accuracy representation offers an appealing solution to the complex modelling problem.Efficient and robust accuracy compensation algorithms have been developed under the framework of artificial neural networks. The ANN-based algorithms provide constant-time inverse compensation therefore are suitable for on-line implementation. Both path compensation and compensation near robot singularity were tackled using the new algorithm.A novel autonomous calibration tool was developed using a trigger probe and a constraint plane. The new method eliminates any use of external measuring devices to determine robot end-effector location measurements, enabling the robot to perform self-calibration on a production line. Robot accuracy was improved to the level of its repeatability within the local calibration volume using the new calibration scheme, which is consistent with the results from using a precision external measuring device, in this case a Coordinate Measuring Machine (CMM)