Étalonnage des machines-outils à cinq axes : configuration optimisée des artefacts et de la séquence de mesure de la méthode SAMBA en vue d'une estimation efficace des erreurs géométriques

RÉSUMÉ Les machines-outils à commande numérique (MOCN) sont assujetties à plusieurs sources d’erreurs, entre autres géométriques, thermiques et dynamiques qui peuvent contribuer à la dégradation de leurs performances. Une attention particulière est prêtée à l’usinage multi axes où le mouvement simultané des axes prismatiques et rotatifs engendre une erreur de positionnement et d’orientation de l’outil par rapport au point à usiner sur la pièce. Des moyens d’évaluations de ces erreurs et de leurs causes, à des fins de maintenance et de compensation, sont alors à développer en tenant compte des aspects économiques, techniques et humains. Il s’agit en particulier de minimiser les temps de mesures qui résultent en des arrêts de production et par conséquent des coûts indirects à éviter à l’entreprise. Le but de la présente thèse est d’améliorer la précision d’une machine-outil à cinq axes à travers l’optimisation d’une technique d’étalonnage existante. En vue de prédire au mieux le comportement de la machine, l’élaboration d’une routine d’inspection adéquate est nécessaire. Ceci comprend un positionnement optimal des éléments du dispositif de mesure, sous forme de billes de référence, ainsi qu’une planification judicieuse des poses de palpage dans l’espace de travail. Une approche analytique basée sur un algorithme d’échange pour la conception d’un plan D-optimal est adoptée pour générer des scénarios d’étalonnage en fonction des écarts géométriques à estimer, modélisés sous forme de polynôme, et du nombre d’inconnues définissant le modèle de la machine. L’évaluation de la pertinence des tests est effectuée à partir d’une étude comparative de critères appelés communément en robotique, indices d’observabilité, issus de l’analyse de la matrice jacobienne d’identification. La qualité prédictive des séquences de mesures générées par simulation est validée en deux étapes : la première consiste en des expériences de répétabilité des tests optimisés imbriqués, la deuxième est une analyse de l’incertitude sur les tests et les paramètres d’erreurs identifiés. Une validation par mesure directe d’une cale calibrée, montée sur la table de la machine, permet de confirmer les résultats qualitatifs fournis par l’indice d’observabilité et ceux quantitatifs déduits de l’estimation de l’incertitude. Les résultats montrent que les routines de vérification proposées sont capables de donner une description complète de la géométrie imparfaite de la machine en incluant les écarts de membrures et les écarts cinématiques. Une amélioration de 55.7% de la valeur de l’indice d’observabilité est constatée par rapport à celle de la stratégie de mesure utilisée présentement dans le laboratoire.----------ABSTRACT Numerically controlled machine tools are prone to potential geometric, thermal and dynamic errors that can have a negative impact on their performance. A careful attention is paid to multi-axis machining where the simultaneous movement of prismatic and rotary axes lead to a positioning and orientation deviation of the tool relative to the workpiece. Tools for assessing these errors and their causes, for maintenance and compensation purposes, are to be developed while taking into consideration economic, technical and human aspects. In particular, this involves minimizing the measurement duration which results in production downtimes and consequently indirect costs to be avoided by the company. This thesis aims to improve the accuracy of a five-axis machine tool through the optimization of an existing calibration technique. For a better prediction of the machine tool erroneous behavior, an adequate inspection routine is sought. This includes optimal positioning of the measuring device components, i.e. master balls, as well as a wise planning of the probing poses in the working volume. An analytical approach based on an exchange algorithm for a D-optimal design is carried out to generate calibration scenarios based on the estimated geometric errors, described as ordinary polynomials, and the number of unknowns predefined in the machine model. The evaluation of the optimized tests suitability relies on a comparison of criteria, commonly known in the robotics field as observability indices and are the outcome of the identification Jacobian matrix analysis. Simulation results are validated in two steps: the first one consists of a repeatability testing of nested optimized probing sequences while the second one is an analysis of the estimated uncertainty on the overall tests and the identified error parameters. Validation via a direct measuring of a calibrated gauge block, mounted on the machine workpiece, confirms the qualitative results provided by the observability index and the quantitative ones concluded from the uncertainty estimation. The outcome suggests that the proposed geometric model updating routines enable a comprehensive description of the machine tool behavior by including location errors and error motions. An improvement of 55.7% of the observability index value is depicted with respect to the currently used measurement strategy. The optimal calibration test duration varies between 30 minutes while probing one master ball for axes location errors identification and 2 hours and 18 minutes for the estimation of both axes location errors and error motions while measuring an artefact of three master balls

Étalonnage de robots industriels à l'aide d'un système portable de photogrammétrie

Le présent travail a pour objectif de valider la pertinence de l’utilisation d’un appareil de photogrammétrie portable dans le domaine de l’étalonnage de robots industriels. L’appareil à l’étude est le système MaxSHOT 3D de Creaform. L’étalonnage est un procédé permettant l’identification d’un modèle géométrique ou non géométrique. Celui-ci permet d’améliorer le contrôle d’un robot afin d’augmenter sa précision de positionnement. Ce mémoire présente le processus d’étalonnage non géométrique d’un robot de petite taille, le LR Mate 200iC de la compagnie FANUC. À des fins de comparaison, la procédure d’étalonnage est adaptée pour considérer un deuxième appareil de mesures 3D, soit le Laser Tracker ION de la compagnie FARO. Ce dernier est aussi utilisé pour construire une banque de validation d’environ 1000 configurations. Les efforts sont d’abord dirigés vers la modélisation du robot à l’étude. Des modèles cinématiques direct et inverse sont présentés respectant le standard de Denavit-Hartenberg modifié (DHM). L’algorithme de Newton-Euler est utilisé pour ajouter une considération non géométrique qui estime les articulations telles des ressorts de torsion. Dans un volet subséquent, l’appareil de photogrammétrie portable et le laser de poursuite sont présentés. Les fonctionnements de ces deux systèmes diamétralement opposés à plusieurs niveaux sont comparés. En effet, le système de photogrammétrie portable est abordable (environ 27 000 $CA), simple d’utilisation et permet l’observation d’une scène. Par contre, il nécessite que les objets à mesurer soient immobiles, requiert un grand nombre de manipulations et n’est pas autonome. En contrepartie, le laser de poursuite permet de mesurer des trajectoires en continu et permet l’automatisation du processus d’acquisition. Néanmoins, l’appareil est très dispendieux (100 000$ CA et plus), ne permet la mesure que d’un seul point à la fois et est sensible aux conditions de l’environnement (température, vibrations, courants d’air, etc.). En prenant compte des contraintes des deux appareils, un algorithme générant des configurations partiellement aléatoires est utilisé pour préparer un bassin de 1000 configurations du robot. L’algorithme s’assure que l’orientation de l’effecteur permet l’acquisition de données par les deux appareils de mesure pour chaque configuration proposée. Dans la phase suivante, une sélection par indice d’observabilité est utilisée afin de déterminer les meilleures configurations à utiliser pour l’identification des paramètres du robot. Le nombre de configurations sélectionnées est de 34, laissant les 966 autres configurations disponibles pour la phase de validation. Le dernier volet du mémoire présente la procédure d’identification de paramètres du robot par la méthode des moindres carrés. Les modèles identifiés sont présentés et leurs performances sont validées. Lorsque les données acquises à partir du MaxSHOT 3D sont utilisées, la précision de positionnement obtenue est de 0.469 mm, tandis qu’elle est de 0.365 mm en utilisant les données du Laser Tracker ION. Néanmoins, comme les mesures utilisées en validation sont issues du laser de poursuite, un biais favorise ce dernier. Pour cette raison et la proximité qui existe entre la précision obtenue avec les deux appareils, il est conclu que relativement à la précision absolue, les deux appareils sont similaires. Il est toutefois suggéré de prendre en compte toutes les autres caractéristiques de chaque appareil, car leur intégration possède des défis bien différents

Visual guidance of unmanned aerial manipulators

The ability to fly has greatly expanded the possibilities for robots to perform surveillance, inspection or map generation tasks. Yet it was only in recent years that research in aerial robotics was mature enough to allow active interactions with the environment. The robots responsible for these interactions are called aerial manipulators and usually combine a multirotor platform and one or more robotic arms. The main objective of this thesis is to formalize the concept of aerial manipulator and present guidance methods, using visual information, to provide them with autonomous functionalities. A key competence to control an aerial manipulator is the ability to localize it in the environment. Traditionally, this localization has required external infrastructure of sensors (e.g., GPS or IR cameras), restricting the real applications. Furthermore, localization methods with on-board sensors, exported from other robotics fields such as simultaneous localization and mapping (SLAM), require large computational units becoming a handicap in vehicles where size, load, and power consumption are important restrictions. In this regard, this thesis proposes a method to estimate the state of the vehicle (i.e., position, orientation, velocity and acceleration) by means of on-board, low-cost, light-weight and high-rate sensors. With the physical complexity of these robots, it is required to use advanced control techniques during navigation. Thanks to their redundancy on degrees-of-freedom, they offer the possibility to accomplish not only with mobility requirements but with other tasks simultaneously and hierarchically, prioritizing them depending on their impact to the overall mission success. In this work we present such control laws and define a number of these tasks to drive the vehicle using visual information, guarantee the robot integrity during flight, and improve the platform stability or increase arm operability. The main contributions of this research work are threefold: (1) Present a localization technique to allow autonomous navigation, this method is specifically designed for aerial platforms with size, load and computational burden restrictions. (2) Obtain control commands to drive the vehicle using visual information (visual servo). (3) Integrate the visual servo commands into a hierarchical control law by exploiting the redundancy of the robot to accomplish secondary tasks during flight. These tasks are specific for aerial manipulators and they are also provided. All the techniques presented in this document have been validated throughout extensive experimentation with real robotic platforms.La capacitat de volar ha incrementat molt les possibilitats dels robots per a realitzar tasques de vigilància, inspecció o generació de mapes. Tot i això, no és fins fa pocs anys que la recerca en robòtica aèria ha estat prou madura com per començar a permetre interaccions amb l’entorn d’una manera activa. Els robots per a fer-ho s’anomenen manipuladors aeris i habitualment combinen una plataforma multirotor i un braç robòtic. L’objectiu d’aquesta tesi és formalitzar el concepte de manipulador aeri i presentar mètodes de guiatge, utilitzant informació visual, per dotar d’autonomia aquest tipus de vehicles. Una competència clau per controlar un manipulador aeri és la capacitat de localitzar-se en l’entorn. Tradicionalment aquesta localització ha requerit d’infraestructura sensorial externa (GPS, càmeres IR, etc.), limitant així les aplicacions reals. Pel contrari, sistemes de localització exportats d’altres camps de la robòtica basats en sensors a bord, com per exemple mètodes de localització i mapejat simultànis (SLAM), requereixen de gran capacitat de còmput, característica que penalitza molt en vehicles on la mida, pes i consum elèctric son grans restriccions. En aquest sentit, aquesta tesi proposa un mètode d’estimació d’estat del robot (posició, velocitat, orientació i acceleració) a partir de sensors instal·lats a bord, de baix cost, baix consum computacional i que proporcionen mesures a alta freqüència. Degut a la complexitat física d’aquests robots, és necessari l’ús de tècniques de control avançades. Gràcies a la seva redundància de graus de llibertat, aquests robots ens ofereixen la possibilitat de complir amb els requeriments de mobilitat i, simultàniament, realitzar tasques de manera jeràrquica, ordenant-les segons l’impacte en l’acompliment de la missió. En aquest treball es presenten aquestes lleis de control, juntament amb la descripció de tasques per tal de guiar visualment el vehicle, garantir la integritat del robot durant el vol, millorar de l’estabilitat del vehicle o augmentar la manipulabilitat del braç. Aquesta tesi es centra en tres aspectes fonamentals: (1) Presentar una tècnica de localització per dotar d’autonomia el robot. Aquest mètode està especialment dissenyat per a plataformes amb restriccions de capacitat computacional, mida i pes. (2) Obtenir les comandes de control necessàries per guiar el vehicle a partir d’informació visual. (3) Integrar aquestes accions dins una estructura de control jeràrquica utilitzant la redundància del robot per complir altres tasques durant el vol. Aquestes tasques son específiques per a manipuladors aeris i també es defineixen en aquest document. Totes les tècniques presentades en aquesta tesi han estat avaluades de manera experimental amb plataformes robòtiques real

POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments

In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method uses as input the current pose of an agent (e.g. a robot) and a RGB-D frame. The task is to plan the next move that brings the agent closer to the target object. We model this problem as a Partially Observable Markov Decision Process solved by a Monte-Carlo planning approach. This allows us to make decisions on the next moves by iterating over the known scenario at hand, exploring the environment and searching for the object at the same time. Differently from the current state of the art in Reinforcement Learning, POMP does not require extensive and expensive (in time and computation) labelled data so being very agile in solving AVS in small and medium real scenarios. We only require the information of the floormap of the environment, an information usually available or that can be easily extracted from an a priori single exploration run. We validate our method on the publicly available AVD benchmark, achieving an average success rate of 0.76 with an average path length of 17.1, performing close to the state of the art but without any training needed. Additionally, we show experimentally the robustness of our method when the quality of the object detection goes from ideal to faulty

Development of Two Cooperative Stewart Platforms for Machining

Ph.DDOCTOR OF PHILOSOPH

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

System Development of an Unmanned Ground Vehicle and Implementation of an Autonomous Navigation Module in a Mine Environment

There are numerous benefits to the insights gained from the exploration and exploitation of underground mines. There are also great risks and challenges involved, such as accidents that have claimed many lives. To avoid these accidents, inspections of the large mines were carried out by the miners, which is not always economically feasible and puts the safety of the inspectors at risk. Despite the progress in the development of robotic systems, autonomous navigation, localization and mapping algorithms, these environments remain particularly demanding for these systems. The successful implementation of the autonomous unmanned system will allow mine workers to autonomously determine the structural integrity of the roof and pillars through the generation of high-fidelity 3D maps. The generation of the maps will allow the miners to rapidly respond to any increasing hazards with proactive measures such as: sending workers to build/rebuild support structure to prevent accidents. The objective of this research is the development, implementation and testing of a robust unmanned ground vehicle (UGV) that will operate in mine environments for extended periods of time. To achieve this, a custom skid-steer four-wheeled UGV is designed to operate in these challenging underground mine environments. To autonomously navigate these environments, the UGV employs the use of a Light Detection and Ranging (LiDAR) and tactical grade inertial measurement unit (IMU) for the localization and mapping through a tightly-coupled LiDAR Inertial Odometry via Smoothing and Mapping framework (LIO-SAM). The autonomous navigation module was implemented based upon the Fast likelihood-based collision avoidance with an extension to human-guided navigation and a terrain traversability analysis framework. In order to successfully operate and generate high-fidelity 3D maps, the system was rigorously tested in different environments and terrain to verify its robustness. To assess the capabilities, several localization, mapping and autonomous navigation missions were carried out in a coal mine environment. These tests allowed for the verification and tuning of the system to be able to successfully autonomously navigate and generate high-fidelity maps

The development and evaluation of computer vision algorithms for the control of an autonomous horticultural vehicle

Economic and environmental pressures have led to a demand for reduced chemical use in crop production. In response to this, precision agriculture techniques have been developed that aim to increase the efficiency of farming operations by more targeted application of chemical treatment. The concept of plant scale husbandry (PSH) has emerged as the logical extreme of precision techniques, where crop and weed plants are treated on an individual basis. To investigate the feasibility of PSH, an autonomous horticultural vehicle has been developed at the Silsoe Research Institute. This thesis describes the development of computer vision algorithms for the experimental vehicle which aim to aid navigation in the field and also allow differential treatment of crop and weed. The algorithm, based upon an extended Kalman filter, exploits the semi-structured nature of the field environment in which the vehicle operates, namely the grid pattern formed by the crop planting. By tracking this grid pattern in the images captured by the vehicles camera as it traverses the field, it is possible to extract information to aid vehicle navigation, such as bearing and offset from the grid of plants. The grid structure can also act as a cue for crop/weed discrimination on the basis of plant position on the ground plane. In addition to tracking the grid pattern, the Kalman filter also estimates the mean distances between the rows of lines and plants in the grid, to cater for variations in the planting procedure. Experiments are described which test the localisation accuracy of the algorithms in offline trials with data captured from the vehicle's camera, and on-line in both a simplified testbed environment and the field. It is found that the algorithms allow safe navigation along the rows of crop. Further experiments demonstrate the crop/weed discrimination performance of the algorithm, both off-line and on-line in a crop treatment experiment performed in the field where all of the crop plants are correctly targeted and no weeds are mistakenly treated