Enhanced Image-Based Visual Servoing Dealing with Uncertainties

Nowadays, the applications of robots in industrial automation have been considerably increased. There is increasing demand for the dexterous and intelligent robots that can work in unstructured environment. Visual servoing has been developed to meet this need by integration of vision sensors into robotic systems. Although there has been significant development in visual servoing, there still exist some challenges in making it fully functional in the industry environment. The nonlinear nature of visual servoing and also system uncertainties are part of the problems affecting the control performance of visual servoing. The projection of 3D image to 2D image which occurs in the camera creates a source of uncertainty in the system. Another source of uncertainty lies in the camera and robot manipulator's parameters. Moreover, limited field of view (FOV) of the camera is another issues influencing the control performance. There are two main types of visual servoing: position-based and image-based. This project aims to develop a series of new methods of image-based visual servoing (IBVS) which can address the nonlinearity and uncertainty issues and improve the visual servoing performance of industrial robots. The first method is an adaptive switch IBVS controller for industrial robots in which the adaptive law deals with the uncertainties of the monocular camera in eye-in-hand configuration. The proposed switch control algorithm decouples the rotational and translational camera motions and decomposes the IBVS control into three separate stages with different gains. This method can increase the system response speed and improve the tracking performance of IBVS while dealing with camera uncertainties. The second method is an image feature reconstruction algorithm based on the Kalman filter which is proposed to handle the situation where the image features go outside the camera's FOV. The combination of the switch controller and the feature reconstruction algorithm can not only improve the system response speed and tracking performance of IBVS, but also can ensure the success of servoing in the case of the feature loss. Next, in order to deal with the external disturbance and uncertainties due to the depth of the features, the third new control method is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6-DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and depth uncertainties. In the last stage of the thesis, the fourth new semi off-line trajectory planning method is developed to perform IBVS tasks for a 6-DOF robotic manipulator system. In this method, the camera's velocity screw is parametrized using time-based profiles. The parameters of the velocity profile are then determined such that the velocity profile takes the robot to its desired position. This is done by minimizing the error between the initial and desired features. The algorithm for planning the orientation of the robot is decoupled from the position planning of the robot. This allows a convex optimization problem which lead to a faster and more efficient algorithm. The merit of the proposed method is that it respects all of the system constraints. This method also considers the limitation caused by camera's FOV. All the developed algorithms in the thesis are validated via tests on a 6-DOF Denso robot in an eye-in-hand configuration

Boosting Performance of Visual Servoing Using Deep Reinforcement Learning From Multiple Demonstrations

In this study, knowledge of multiple controllers was used and combined with deep reinforcement learning (RL) to train a visual servoing (VS) technique. Deep RL algorithms were successful in solving complicated control problems, however they generally require a large amount of data before they achieve an acceptable performance. We developed a method that generates online hyper-volume action bounds from demonstrations of multiple controllers (experts) to address the issue of insufficient data in RL. The agent then continues to explore the created bounds to find more optimized solutions and gain more rewards. By doing this, we cut out pointless agent explorations, which results in a reduction in training time as well as an improvement in performance of the trained policy. During the training process, we used domain randomization and domain adaptation to make the VS approach robust in the real world. As a result, we showed a 51% decrease in training time to achieve the desired level of performance, compared to the case when RL was used solely. The findings showed that the developed method outperformed other baseline VS methods (image-based VS, position-based VS, and hybrid-decoupled VS) in terms of VS error convergence speed and maintained higher manipulability

Robot Visual Servoing Using Discontinuous Control

This work presents different proposals to deal with common problems in robot visual servoing based on the application of discontinuous control methods. The feasibility and effectiveness of the proposed approaches are substantiated by simulation results and real experiments using a 6R industrial manipulator. The main contributions are: - Geometric invariance using sliding mode control (Chapter 3): the defined higher-order invariance is used by the proposed approaches to tackle problems in visual servoing. Proofs of invariance condition are presented. - Fulfillment of constraints in visual servoing (Chapter 4): the proposal uses sliding mode methods to satisfy mechanical and visual constraints in visual servoing, while a secondary task is considered to properly track the target object. The main advantages of the proposed approach are: low computational cost, robustness and fully utilization of the allowed space for the constraints. - Robust auto tool change for industrial robots using visual servoing (Chapter 4): visual servoing and the proposed method for constraints fulfillment are applied to an automated solution for tool changing in industrial robots. The robustness of the proposed method is due to the control law of the visual servoing, which uses the information acquired by the vision system to close a feedback control loop. Furthermore, sliding mode control is simultaneously used in a prioritized level to satisfy the aforementioned constraints. Thus, the global control accurately places the tool in the warehouse, but satisfying the robot constraints. - Sliding mode controller for reference tracking (Chapter 5): an approach based on sliding mode control is proposed for reference tracking in robot visual servoing using industrial robot manipulators. The novelty of the proposal is the introduction of a sliding mode controller that uses a high-order discontinuous control signal, i.e., joint accelerations or joint jerks, in order to obtain a smoother behavior and ensure the robot system stability, which is demonstrated with a theoretical proof. - PWM and PFM for visual servoing in fully decoupled approaches (Chapter 6): discontinuous control based on pulse width and pulse frequency modulation is proposed for fully decoupled position based visual servoing approaches, in order to get the same convergence time for camera translation and rotation. Moreover, other results obtained in visual servoing applications are also described.Este trabajo presenta diferentes propuestas para tratar problemas habituales en el control de robots por realimentación visual, basadas en la aplicación de métodos de control discontinuos. La viabilidad y eficacia de las propuestas se fundamenta con resultados en simulación y con experimentos reales utilizando un robot manipulador industrial 6R. Las principales contribuciones son: - Invariancia geométrica utilizando control en modo deslizante (Capítulo 3): la invariancia de alto orden definida aquí es utilizada después por los métodos propuestos, para tratar problemas en control por realimentación visual. Se apuertan pruebas teóricas de la condición de invariancia. - Cumplimiento de restricciones en control por realimentación visual (Capítulo 4): esta propuesta utiliza métodos de control en modo deslizante para satisfacer restricciones mecánicas y visuales en control por realimentación visual, mientras una tarea secundaria se encarga del seguimiento del objeto. Las principales ventajas de la propuesta son: bajo coste computacional, robustez y plena utilización del espacio disponible para las restricciones. - Cambio de herramienta robusto para un robot industrial mediante control por realimentación visual (Capítulo 4): el control por realimentación visual y el método propuesto para el cumplimiento de las restricciones se aplican a una solución automatizada para el cambio de herramienta en robots industriales. La robustez de la propuesta radica en el uso del control por realimentación visual, que utiliza información del sistema de visión para cerrar el lazo de control. Además, el control en modo deslizante se utiliza simultáneamente en un nivel de prioridad superior para satisfacer las restricciones. Así pues, el control es capaz de dejar la herramienta en el intercambiador de herramientas de forma precisa, a la par que satisface las restricciones del robot. - Controlador en modo deslizante para seguimiento de referencia (Capítulo 5): se propone un enfoque basado en el control en modo deslizante para seguimiento de referencia en robots manipuladores industriales controlados por realimentación visual. La novedad de la propuesta radica en la introducción de un controlador en modo deslizante que utiliza la señal de control discontinua de alto orden, i.e. aceleraciones o jerks de las articulaciones, para obtener un comportamiento más suave y asegurar la estabilidad del sistema robótico, lo que se demuestra con una prueba teórica. - Control por realimentación visual mediante PWM y PFM en métodos completamente desacoplados (Capítulo 6): se propone un control discontinuo basado en modulación del ancho y frecuencia del pulso para métodos completamente desacoplados de control por realimentación visual basados en posición, con el objetivo de conseguir el mismo tiempo de convergencia para los movimientos de rotación y traslación de la cámara . Además, se presentan también otros resultados obtenidos en aplicaciones de control por realimentación visual.Aquest treball presenta diferents propostes per a tractar problemes habituals en el control de robots per realimentació visual, basades en l'aplicació de mètodes de control discontinus. La viabilitat i eficàcia de les propostes es fonamenta amb resultats en simulació i amb experiments reals utilitzant un robot manipulador industrial 6R. Les principals contribucions són: - Invariància geomètrica utilitzant control en mode lliscant (Capítol 3): la invariància d'alt ordre definida ací és utilitzada després pels mètodes proposats, per a tractar problemes en control per realimentació visual. S'aporten proves teòriques de la condició d'invariància. - Compliment de restriccions en control per realimentació visual (Capítol 4): aquesta proposta utilitza mètodes de control en mode lliscant per a satisfer restriccions mecàniques i visuals en control per realimentació visual, mentre una tasca secundària s'encarrega del seguiment de l'objecte. Els principals avantatges de la proposta són: baix cost computacional, robustesa i plena utilització de l'espai disponible per a les restriccions. - Canvi de ferramenta robust per a un robot industrial mitjançant control per realimentació visual (Capítol 4): el control per realimentació visual i el mètode proposat per al compliment de les restriccions s'apliquen a una solució automatitzada per al canvi de ferramenta en robots industrials. La robustesa de la proposta radica en l'ús del control per realimentació visual, que utilitza informació del sistema de visió per a tancar el llaç de control. A més, el control en mode lliscant s'utilitza simultàniament en un nivell de prioritat superior per a satisfer les restriccions. Així doncs, el control és capaç de deixar la ferramenta en l'intercanviador de ferramentes de forma precisa, a la vegada que satisfà les restriccions del robot. - Controlador en mode lliscant per a seguiment de referència (Capítol 5): es proposa un enfocament basat en el control en mode lliscant per a seguiment de referència en robots manipuladors industrials controlats per realimentació visual. La novetat de la proposta radica en la introducció d'un controlador en mode lliscant que utilitza senyal de control discontínua d'alt ordre, i.e. acceleracions o jerks de les articulacions, per a obtindre un comportament més suau i assegurar l'estabilitat del sistema robòtic, la qual cosa es demostra amb una prova teòrica. - Control per realimentació visual mitjançant PWM i PFM en mètodes completament desacoblats (Capítol 6): es proposa un control discontinu basat en modulació de l'ample i la freqüència del pols per a mètodes completament desacoblats de control per realimentació visual basats en posició, amb l'objectiu d'aconseguir el mateix temps de convergència per als moviments de rotació i translació de la càmera. A més, es presenten també altres resultats obtinguts en aplicacions de control per realimentació visual.Muñoz Benavent, P. (2017). Robot Visual Servoing Using Discontinuous Control [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90430TESI

A hybrid switched reactive-based visual servo control of 5-DOF robot manipulators for pick-and-place tasks

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Visual Servoing in Robotics

Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas

Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach

Visual Servoing

International audienceThis chapter introduces visual servo control, using computer vision data in the servo loop to control the motion of a robot. We first describe the basic techniques that are by now well established in the field. We give a general overview of the formulation of the visual servo control problem, and describe the two archetypal visual servo control schemes: image-based and pose-based visual servo control. We then discuss performance and stability issues that pertain to these two schemes, motivating advanced techniques. Of the many advanced techniques that have been developed , we discuss 2.5-D, hybrid, partitioned, and switched approaches. Having covered a variety of control schemes, we deal with target tracking and controlling motion directly in the joint space and extensions to under-actuated ground and aerial robots. We conclude by describing applications of visual ser-voing in robotics

GNC architecture solutions for robust operations of a free-floating space manipulator via image based visual servoing

On-orbit servicing often requires the use of robotic arms, and a key asset in this kind of operations is autonomy. In this framework, the use of optical devices is a solution, already analyzed in many researches both for autonomous rendezvous and docking and for the evaluation of the control of the manipulator. In the present paper, simulations for assessing the controller performance are realized in a high-fidelity purposely developed software architecture, in which not only the selected 6 DOF space manipulator is modeled, but also a virtual camera, acquiring in the loop images of the target CAD model imported, is included in the GNC loop. This approach allows to emphasis several problems that would not emerge in simulations with images characterized by easily-identifiable, purposely-created markers. At the scope, a specific GNC architecture is developed, based on finite-state machine logic. According to this approach, two different Image Based Visual Servoing strategies are alternatively performed, commanding only linear or angular velocity of the camera, switching between the two control techniques when the “stack” or “divergence” condition is triggered. In this way a stable and robust accomplishment of the tasks is achieved for many configurations and for different target models

A Hyper-network Based End-to-end Visual Servoing with Arbitrary Desired Poses

Recently, several works achieve end-to-end visual servoing (VS) for robotic manipulation by replacing traditional controller with differentiable neural networks, but lose the ability to servo arbitrary desired poses. This letter proposes a differentiable architecture for arbitrary pose servoing: a hyper-network based neural controller (HPN-NC). To achieve this, HPN-NC consists of a hyper net and a low-level controller, where the hyper net learns to generate the parameters of the low-level controller and the controller uses the 2D keypoints error for control like traditional image-based visual servoing (IBVS). HPN-NC can complete 6 degree of freedom visual servoing with large initial offset. Taking advantage of the fully differentiable nature of HPN-NC, we provide a three-stage training procedure to servo real world objects. With self-supervised end-to-end training, the performance of the integrated model can be further improved in unseen scenes and the amount of manual annotations can be significantly reduced