Survey of Visual and Force/Tactile Control of Robots for Physical Interaction in Spain

Sensors provide robotic systems with the information required to perceive the changes that happen in unstructured environments and modify their actions accordingly. The robotic controllers which process and analyze this sensory information are usually based on three types of sensors (visual, force/torque and tactile) which identify the most widespread robotic control strategies: visual servoing control, force control and tactile control. This paper presents a detailed review on the sensor architectures, algorithmic techniques and applications which have been developed by Spanish researchers in order to implement these mono-sensor and multi-sensor controllers which combine several sensors

MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL

[EN] This thesis deals with two characteristic problems in visual feedback robot control: 1) sensor latency; 2) providing suitable trajectories for the robot and for the measurement in the image. All the approaches presented in this work are analyzed and implemented on a 6 DOF industrial robot manipulator or/and a wheeled robot. Focusing on the sensor latency problem, this thesis proposes the use of dual-rate high order holds within the control loop of robots. In this sense, the main contributions are: - Dual-rate high order holds based on primitive functions for robot control (Chapter 3): analysis of the system performance with and without the use of this multi-rate technique from non-conventional control. In addition, as consequence of the use of dual-rate holds, this work obtains and validates multi-rate controllers, especially dual-rate PIDs. - Asynchronous dual-rate high order holds based on primitive functions with time delay compensation (Chapter 3): generalization of asynchronous dual-rate high order holds incorporating an input signal time delay compensation component, improving thus the inter-sampling estimations computed by the hold. It is provided an analysis of the properties of such dual-rate holds with time delay compensation, comparing them with estimations obtained by the equivalent dual-rate holds without this compensation, as well as their implementation and validation within the control loop of a 6 DOF industrial robot manipulator. - Multi-rate nonlinear high order holds (Chapter 4): generalization of the concept of dual-rate high order holds with nonlinear estimation models, which include information about the plant to be controlled, the controller(s) and sensor(s) used, obtained from machine learning techniques. Thus, in order to obtain such a nonlinear hold, it is described a methodology non dependent of the machine technique used, although validated using artificial neural networks. Finally, an analysis of the properties of these new holds is carried out, comparing them with their equivalents based on primitive functions, as well as their implementation and validation within the control loop of an industrial robot manipulator and a wheeled robot. With respect to the problem of providing suitable trajectories for the robot and for the measurement in the image, this thesis presents the novel reference features filtering control strategy and its generalization from a multi-rate point of view. The main contributions in this regard are: - Reference features filtering control strategy (Chapter 5): a new control strategy is proposed to enlarge significantly the solution task reachability of robot visual feedback control. The main idea is to use optimal trajectories proposed by a non-linear EKF predictor-smoother (ERTS), based on Rauch-Tung-Striebel (RTS) algorithm, as new feature references for an underlying visual feedback controller. In this work it is provided both the description of the implementation algorithm and its implementation and validation utilizing an industrial robot manipulator. - Dual-rate Reference features filtering control strategy (Chapter 5): a generalization of the reference features filtering approach from a multi-rate point of view, and a dual Kalman-smoother step based on the relation of the sensor and controller frequencies of the reference filtering control strategy is provided, reducing the computational cost of the former algorithm, as well as addressing the problem of the sensor latency. The implementation algorithms, as well as its analysis, are described.[ES] La presente tesis propone soluciones para dos problemas característicos de los sistemas robóticos cuyo bucle de control se cierra únicamente empleando sensores de visión artificial: 1) la latencia del sensor; 2) la obtención de trayectorias factibles tanto para el robot así como para las medidas obtenidas en la imagen. Todos los métodos propuestos en este trabajo son analizados, validados e implementados utilizando brazo robot industrial de 6 grados de libertad y/o en un robot con ruedas. Atendiendo al problema de la latencia del sensor, esta tesis propone el uso de retenedores bi-frequencia de orden alto dentro de los lazos de control de robots. En este aspecto las principales contribuciones son: -Retenedores bi-frecuencia de orden alto basados en funciones primitivas dentro de lazos de control de robots (Capítulo 3): análisis del comportamiento del sistema con y sin el uso de esta técnica de control no convencional. Además, como consecuencia del empleo de los retenedores, obtención y validación de controladores multi-frequencia, concretamente de PIDs bi-frecuencia. -Retenedores bi-frecuencia asíncronos de orden alto basados en funciones primitivas con compensación de retardos (Capítulo 3): generalización de los retenedores bi-frecuencia asíncronos de orden alto incluyendo una componente de compensación del retardo en la señal de entrada, mejorando así las estimaciones inter-muestreo calculadas por el retenedor. Se proporciona un análisis de las propiedades de los retenedores con compensación del retardo, comparándolas con las obtenidas por sus predecesores sin compensación, así como su implementación y validación en un brazo robot de 6 grados de libertad. -Retenedores multi-frecuencia no lineales de orden alto (Capítulo 4): generalización del concepto de retenedor bi-frecuencia de orden alto con modelos de estimación no lineales, los cuales incluyen información tanto de la planta a controlar, como del controlador(es) y sensor(es) empleado(s), obtenida a partir de técnicas de aprendizaje. Así pues, para obtener dicho retenedor no lineal, se describe una metodología independiente de la herramienta de aprendizaje utilizada, aunque validada con el uso de redes neuronales artificiales. Finalmente se realiza un análisis de las propiedades de estos nuevos retenedores, comparándolos con sus predecesores basados en funciones primitivas, así como su implementación y validación en un brazo robot de 6 grados de libertad y en un robot móvil con ruedas. Por lo que respecta al problema de generación de trayectorias factibles para el robot y para la medida en la imagen, esta tesis propone la nueva estrategia de control basada en el filtrado de la referencia y su generalización desde el punto de vista multi-frecuencial. -Estrategia de control basada en el filtrado de la referencia (Capítulo 5): una nueva estrategia de control se propone para ampliar significativamente el espacio de soluciones de los sistemas robóticos realimentados con sensores de visión artificial. La principal idea es utilizar las trayectorias óptimas obtenidas por una trayectoria predicha por un filtro de Kalman seguido de un suavizado basado en el algoritmo Rauch-Tung-Striebel (RTS) como nuevas referencias para un controlador dado. En este trabajo se proporciona tanto la descripción del algoritmo como su implementación y validación empleando un brazo robótico industrial. -Estrategia de control bi-frecuencia basada en el filtrado de la referencia (Capítulo 5): generalización de la estrategia de control basada en filtrado de la referencia desde un punto de vista multi-frecuencial, con un filtro de Kalman multi-frecuencia y un Kalman-smoother dual basado en la relación existente entre las frecuencias del sensor y del controlador, reduciendo así el coste computacional del algoritmo y, al mismo tiempo, dando solución al problema de la latencia del sensor. La validación se realiza utilizando un barzo robot industria asi[CA] La present tesis proposa solucions per a dos problemes característics dels sistemes robòtics el els que el bucle de control es tanca únicament utilitzant sensors de visió artificial: 1) la latència del sensor; 2) l'obtenció de trajectòries factibles tant per al robot com per les mesures en la imatge. Tots els mètodes proposats en aquest treball son analitzats, validats e implementats utilitzant un braç robot industrial de 6 graus de llibertat i/o un robot amb rodes. Atenent al problema de la latència del sensor, esta tesis proposa l'ús de retenidors bi-freqüència d'ordre alt a dins del llaços de control de robots. Al respecte, les principals contribucions son: - Retenidors bi-freqüència d'ordre alt basats en funcions primitives a dintre dels llaços de control de robots (Capítol 3): anàlisis del comportament del sistema amb i sense l'ús d'aquesta tècnica de control no convencional. A més a més, com a conseqüència de l'ús dels retenidors, obtenció i validació de controladors multi-freqüència, concretament de PIDs bi-freqüència. - Retenidors bi-freqüència asíncrons d'ordre alt basats en funcions primitives amb compensació de retards (Capítol 3): generalització dels retenidors bi-freqüència asíncrons d'ordre alt inclouen una component de compensació del retràs en la senyal d'entrada al retenidor, millorant així les estimacions inter-mostreig calculades per el retenidor. Es proporciona un anàlisis de les propietats dels retenidors amb compensació del retràs, comparant-les amb les obtingudes per el seus predecessors sense la compensació, així com la seua implementació i validació en un braç robot industrial de 6 graus de llibertat. - Retenidors multi-freqüència no-lineals d'ordre alt (Capítol 4): generalització del concepte de retenidor bi-freqüència d'ordre alt amb models d'estimació no lineals, incloent informació tant de la planta a controlar, com del controlador(s) i sensor(s) utilitzat(s), obtenint-la a partir de tècniques d'aprenentatge. Així doncs, per obtindre el retenidor no lineal, es descriu una metodologia independent de la ferramenta d'aprenentatge utilitzada, però validada amb l'ús de rets neuronals artificials. Finalment es realitza un anàlisis de les propietats d'aquestos nous retenidors, comparant-los amb els seus predecessors basats amb funcions primitives, així com la seua implementació i validació amb un braç robot de 6 graus de llibertat i amb un robot mòbil de rodes. Per el que respecta al problema de generació de trajectòries factibles per al robot i per la mesura en la imatge, aquesta tesis proposa la nova estratègia de control basada amb el filtrat de la referència i la seua generalització des de el punt de vista multi-freqüència. - Estratègia de control basada amb el filtrat de la referència (Capítol 5): una nova estratègia de control es proposada per ampliar significativament l'espai de solucions dels sistemes robòtics realimentats amb sensors de visió artificial. La principal idea es la d'utilitzar les trajectòries optimes obtingudes per una trajectòria predita per un filtre de Kalman seguit d'un suavitzat basat en l'algoritme Rauch-Tung-Striebel (RTS) com noves referències per a un control donat. En aquest treball es proporciona tant la descripció del algoritme així com la seua implementació i validació utilitzant un braç robòtic industrial de 6 graus de llibertat. - Estratègia de control bi-freqüència basada en el filtrat (Capítol 5): generalització de l'estratègia de control basada am filtrat de la referència des de un punt de vista multi freqüència, amb un filtre de Kalman multi freqüència i un Kalman-Smoother dual basat amb la relació existent entre les freqüències del sensor i del controlador, reduint així el cost computacional de l'algoritme i, al mateix temps, donant solució al problema de la latència del sensor. L'algoritme d'implementació d'aquesta tècnica, així com la seua validaciSolanes Galbis, JE. (2015). MULTI-RATE VISUAL FEEDBACK ROBOT CONTROL [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/57951TESI

Maximum likelihood estimation-assisted ASVSF through state covariance-based 2D SLAM algorithm

The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurementto the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC)

Feature-based motion control for near-repetitive structures

In many manufacturing processes, production steps are carried out on repetitive structures which consist of identical features placed in a repetitive pattern. In the production of these repetitive structures one or more consecutive steps are carried out on the features to create the final product. Key to obtaining a high product quality is to position the tool with respect to each feature of the repetitive structure with a high accuracy. In current industrial practice, local position sensors such as motor encoders are used to separately measure the metric position of the tool and the stage where the repetitive structure is on. Here, the final accuracy of alignment directly relies on assumptions like thermal stability, infinite machine frame stiffness and constant pitch between successive features. As the size of these repetitive structures is growing, often these assumptions are difficult to satisfy in practice. The main goal of this thesis is to design control approaches for accurately positioning the tool with respect to the features, without the need of the aforementioned assumptions. In this thesis, visual servoing, i.e., using machine vision data in the servo loop to control the motion of a system, is used for controlling the relative position between the tool and the features. By using vision as a measurement device the relevant dynamics and disturbances are therefore measurable and can be accounted for in a non-collocated control setting. In many cases, the pitch between features is subject to small imperfections, e.g., due to the finite accuracy of preceding process steps or thermal expansion. Therefore, the distance between two features is unknown a priori, such that setpoints can not be constructed a priori. In this thesis, a novel feature-based position measurement is proposed, with the advantage that the feature-based target position of every feature is known a priori. Motion setpoints can be defined from feature to feature without knowing the exact absolute metric position of the features beforehand. Next to feature-to-feature movements, process steps involving movements with respect to the features, e.g., engraving or cutting, are implemented to increase the versatility of the movements. Final positioning accuracies of 10 µm are attained. For feature-to-feature movements with varying distances between the features a novel feedforward control strategy is developed based on iterative learning control (ILC) techniques. In this case, metric setpoints from feature to feature are constructed by scaling a nominal setpoint to handle the pitch imperfections. These scale varying setpoints will be applied during the learning process, while second order ILC is used to relax the classical ILC boundary of setpoints being the same every trial. The final position accuracy is within 5 µm, while scale varying setpoints are applied. The proposed control design approaches are validated in practice on an industrial application, where the task is to position a tool with respect to discrete semiconductors of a wafer. A visual servoing setup capable of attaining a 1 kHz frame rate is realized. It consists of an xy-stage on which a wafer is clamped which contains the discrete semiconductor products. A camera looks down onto the wafer and is used for position feedback. The time delay of the system is 2.5 ms and the variation of the position measurement is 0.3 µm (3s)

Modified System Design and Implementation of an Intelligent Assistive Robotic Manipulator

This thesis presents three improvements to the current UCF MANUS systems. The first improvement modifies the existing fine motion controller into PI controller that has been optimized to prevent the object from leaving the view of the cameras used for visual servoing. This is achieved by adding a weight matrix to the proportional part of the controller that is constrained by an artificial ROI. When the feature points being used are approaching the boundaries of the ROI, the optimized controller weights are calculated using quadratic programming and added to the nominal proportional gain portion of the controller. The second improvement was a compensatory gross motion method designed to ensure that the desired object can be identified. If the object cannot be identified after the initial gross motion, the end-effector will then be moved to one of three different locations around the object until the object is identified or all possible positions are checked. This framework combines the Kanade-Lucase-Tomasi local tracking method with the ferns global detector/tracker to create a method that utilizes the strengths of both systems to overcome their inherent weaknesses. The last improvement is a particle-filter based tracking algorithm that robustifies the visual servoing function of fine motion. This method performs better than the current global detector/tracker that was being implemented by allowing the tracker to successfully track the object in complex environments with non-ideal conditions

Design and Development of Robotic Part Assembly System under Vision Guidance

Robots are widely used for part assembly across manufacturing industries to attain high productivity through automation. The automated mechanical part assembly system contributes a major share in production process. An appropriate vision guided robotic assembly system further minimizes the lead time and improve quality of the end product by suitable object detection methods and robot control strategies. An approach is made for the development of robotic part assembly system with the aid of industrial vision system. This approach is accomplished mainly in three phases. The first phase of research is mainly focused on feature extraction and object detection techniques. A hybrid edge detection method is developed by combining both fuzzy inference rule and wavelet transformation. The performance of this edge detector is quantitatively analysed and compared with widely used edge detectors like Canny, Sobel, Prewitt, mathematical morphology based, Robert, Laplacian of Gaussian and wavelet transformation based. A comparative study is performed for choosing a suitable corner detection method. The corner detection technique used in the study are curvature scale space, Wang-Brady and Harris method. The successful implementation of vision guided robotic system is dependent on the system configuration like eye-in-hand or eye-to-hand. In this configuration, there may be a case that the captured images of the parts is corrupted by geometric transformation such as scaling, rotation, translation and blurring due to camera or robot motion. Considering such issue, an image reconstruction method is proposed by using orthogonal Zernike moment invariants. The suggested method uses a selection process of moment order to reconstruct the affected image. This enables the object detection method efficient. In the second phase, the proposed system is developed by integrating the vision system and robot system. The proposed feature extraction and object detection methods are tested and found efficient for the purpose. In the third stage, robot navigation based on visual feedback are proposed. In the control scheme, general moment invariants, Legendre moment and Zernike moment invariants are used. The selection of best combination of visual features are performed by measuring the hamming distance between all possible combinations of visual features. This results in finding the best combination that makes the image based visual servoing control efficient. An indirect method is employed in determining the moment invariants for Legendre moment and Zernike moment. These moments are used as they are robust to noise. The control laws, based on these three global feature of image, perform efficiently to navigate the robot in the desire environment

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

From plain visualisation to vibration sensing: using a camera to control the flexibilities in the ITER remote handling equipment

Thermonuclear fusion is expected to play a key role in the energy market during the second half of this century, reaching 20% of the electricity generation by 2100. For many years, fusion scientists and engineers have been developing the various technologies required to build nuclear power stations allowing a sustained fusion reaction. To the maximum possible extent, maintenance operations in fusion reactors are performed manually by qualified workers in full accordance with the "as low as reasonably achievable" (ALARA) principle. However, the option of hands-on maintenance becomes impractical, difficult or simply impossible in many circumstances, such as high biological dose rates. In this case, maintenance tasks will be performed with remote handling (RH) techniques. The International Thermonuclear Experimental Reactor ITER, to be commissioned in southern France around 2025, will be the first fusion experiment producing more power from fusion than energy necessary to heat the plasma. Its main objective is “to demonstrate the scientific and technological feasibility of fusion power for peaceful purposes”. However ITER represents an unequalled challenge in terms of RH system design, since it will be much more demanding and complex than any other remote maintenance system previously designed. The introduction of man-in-the-loop capabilities in the robotic systems designed for ITER maintenance would provide useful assistance during inspection, i.e. by providing the operator the ability and flexibility to locate and examine unplanned targets, or during handling operations, i.e. by making peg-in-hole tasks easier. Unfortunately, most transmission technologies able to withstand the very specific and extreme environmental conditions existing inside a fusion reactor are based on gears, screws, cables and chains, which make the whole system very flexible and subject to vibrations. This effect is further increased as structural parts of the maintenance equipment are generally lightweight and slender structures due to the size and the arduous accessibility to the reactor. Several methodologies aiming at avoiding or limiting the effects of vibrations on RH system performance have been investigated over the past decade. These methods often rely on the use of vibration sensors such as accelerometers. However, reviewing market shows that there is no commercial off-the-shelf (COTS) accelerometer that meets the very specific requirements for vibration sensing in the ITER in-vessel RH equipment (resilience to high total integrated dose, high sensitivity). The customisation and qualification of existing products or investigation of new concepts might be considered. However, these options would inevitably involve high development costs. While an extensive amount of work has been published on the modelling and control of flexible manipulators in the 1980s and 1990s, the possibility to use vision devices to stabilise an oscillating robotic arm has only been considered very recently and this promising solution has not been discussed at length. In parallel, recent developments on machine vision systems in nuclear environment have been very encouraging. Although they do not deal directly with vibration sensing, they open up new prospects in the use of radiation tolerant cameras. This thesis aims to demonstrate that vibration control of remote maintenance equipment operating in harsh environments such as ITER can be achieved without considering any extra sensor besides the embarked rad-hardened cameras that will inevitably be used to provide real-time visual feedback to the operators. In other words it is proposed to consider the radiation-tolerant vision devices as full sensors providing quantitative data that can be processed by the control scheme and not only as plain video feedback providing qualitative information. The work conducted within the present thesis has confirmed that methods based on the tracking of visual features from an unknown environment are effective candidates for the real-time control of vibrations. Oscillations induced at the end effector are estimated by exploiting a simple physical model of the manipulator. Using a camera mounted in an eye-in-hand configuration, this model is adjusted using direct measurement of the tip oscillations with respect to the static environment. The primary contribution of this thesis consists of implementing a markerless tracker to determine the velocity of a tip-mounted camera in an untrimmed environment in order to stabilise an oscillating long-reach robotic arm. In particular, this method implies modifying an existing online interaction matrix estimator to make it self-adjustable and deriving a multimode dynamic model of a flexible rotating beam. An innovative vision-based method using sinusoidal regression to sense low-frequency oscillations is also proposed and tested. Finally, the problem of online estimation of the image capture delay for visual servoing applications with high dynamics is addressed and an original approach based on the concept of cross-correlation is presented and experimentally validated