Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters

The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining.Comment: arXiv admin note: substantial text overlap with arXiv:1211.573

Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters

International audienceThe paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining

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

A surgical system for automatic registration, stiffness mapping and dynamic image overlay

In this paper we develop a surgical system using the da Vinci research kit (dVRK) that is capable of autonomously searching for tumors and dynamically displaying the tumor location using augmented reality. Such a system has the potential to quickly reveal the location and shape of tumors and visually overlay that information to reduce the cognitive overload of the surgeon. We believe that our approach is one of the first to incorporate state-of-the-art methods in registration, force sensing and tumor localization into a unified surgical system. First, the preoperative model is registered to the intra-operative scene using a Bingham distribution-based filtering approach. An active level set estimation is then used to find the location and the shape of the tumors. We use a recently developed miniature force sensor to perform the palpation. The estimated stiffness map is then dynamically overlaid onto the registered preoperative model of the organ. We demonstrate the efficacy of our system by performing experiments on phantom prostate models with embedded stiff inclusions.Comment: International Symposium on Medical Robotics (ISMR 2018

OPTIMALITY CRITERIA FOR MEASUREMENT POSES SELECTION IN CALIBRATION OF ROBOT STIFFNESS PARAMETERS

International audienceThe paper focuses on the accuracy improvement of industrial robots by means of elasto-static parameters calibration. It proposes a new optimality criterion for measurement poses selection in calibration of robot stiffness parameters. This criterion is based on the concept of the manipulator test pose that is defined by the user via the joint angles and the external force. The proposed approach essentially differs from the traditional ones and ensures the best compliance error compensation for the test configuration. The advantages of this approach and its suitability for practical applications are illustrated by numerical examples, which deal with calibration of elasto-static parameters of planar manipulator with rigid links and compliant actuated joints

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