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EN
Visual servoing define a new methodology for vision based control in robotics. Vision based action involve number of actions that move a robot in response of results of camera analysis. This process is important to operate and help robot to achieve a specific goal. The main purpose of visual servoing consists of considering a vision system by specific sensor dedicated to involve control servo loop and task. In this article, three visual control scheme: Image Based Visual Servoing (IBVS), Position Based Visual Servoing (PBVS) and Hybrid Based Visual Servoing (HBVS) are illustrated. The different terminologies are represented through effective workflow of robot vision. IBVS method concentrate on the image features that are immediately available in the image. This experiment is performed by estimating distance between camera and object. PBVS consist of moving object 3-D parameters to estimate measurement. This paper showcases PBVS using kuka robot model. HBVS uses the 2D and 3D servoing by combining visual sensors also it overcomes challenges of previous two methods. This paper represents HBVS method using IPR communication robot model.
EN
In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.
PL
Artykuł przedstawia metodę doboru nastaw serwomechanizmów wizyjnych. Zaproponowano sposób dekompozycji układu sterującego i regulatorów warstwy wyższej oraz przedstawiono proces automatyzujący wyznaczanie wzmocnienia krytycznego. Metodę wykorzystano do doboru nastaw regulatorów P, PI oraz PID dla serwomechanizmu wizyjnego typu PB-EOL-EIH. Zaproponowano również sposób weryfikacji ich działania oraz przeprowadzono serię eksperymentów z wykorzystaniem manipulatora IRp-6, wykazujących poprawność dobranych nastaw.
EN
The article presents a method for tuning controllers utilized in visual servoing. It is based on the ultimate gain determination and decomposition of the control system followed by decomposition of the high level controller. A process automating the determiniation of the gain is proposed. The method is applied for tuning of P, Pl and PID controllers for the PB-EOLE1H visual servo. Finally a conducted series of experiments on real manipulator verify the correctness of developed controller.
4
Content available Specyfikacja struktur serwomechanizmów wizyjnych
PL
W artykule przedstawiono formalną metodę opisu złożonych systemów robotycznych, za pomocą której wyspecyfikowano układy realizujące trzy diametralnie różne zachowania robota: ruch pozycyjny w przestrzeni kartezjańskiej, sterowanie oparte o informację wizyjną pochodzącą z ruchomej kamery zintegrowanej z jego chwytakiem oraz sterowanie wykorzystujące informacje odebraną z nieruchomej kamery. Przedstawione wyniki eksperymentów potwierdzają poprawność stworzonych układów.
EN
The paper presents a formal method of specifying complex robotic systems, applied to the description of three diverse robot behaviors: motion in Cartesian space to a given pose and two types of motions in which the goal was computed on the base of information retrieved from cameras (a camera integrated with the robot gripper and a camera statically mounted above the scene). The presented experimental results confirm the correctness of the developed systems.
EN
In this paper, we present filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, in case of multi-target tracking. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models change during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate tracking. In order to deal with this problem, the IMM algorithm was combined with the Unscented Kalman Filter (UKF). Even if the later algorithm proved its efficacy in nonlinear model case, it presents a serious drawback in the case of non Gaussian noise. To deal with this problem we propose to substitute the UKF with the Particle Filter (PF). To overcome the problem of data association, we propose the use the JPDA approach. To reduce the computational burden of this technique, we choose firstly the most likely feasible events by applying a Genetic Algorithm; finally the derived algorithm from the combination of the IMM-PF algorithm and the GA-JPDA approach is noted GA-JPDA-IMM-PF. To insure a more reduction of the computation complexity of the latter data association approach, we propose a fuzzy data association approach which we combine with the IMM-PF estimator, the derived algorithm is noted fuzzy IMM-PF. Finally the two algorithms are compared according to the target loss rate inferred by each of them.
6
Content available Serwomechanizmy wizyjne - część 2
PL
Obecnie uwaga naukowców zajmujących się robotyką koncentruje się na robotach usługowych oraz terenowych. W obu przypadkach do sprawnego wykonywania zadań roboty te potrzebują mnogości czujników, ale podstawowe stanowią kamery. Są one szczególnie istotne przy chwytaniu. Do realizacji tego zadania trzeba skonstruować serwomechanizm wizyjny.W pierwszej części tego artykułu wprowadzono podstawowe pojęcia niezbędne do analizy struktur serwomechanizmów wizyjnych. Ta część przedstawia poszczególne struktury wraz z analizą ich wad i zalet.
EN
The first part of this paper, published in PAK 5/2006, was devoted to basic concepts used in the analysis of visual-servo control and the classification of the resulting structures of controllers. This part gives a detailed description of each structure. Moreover, it presents the advantages and drawbacks of each of those structures, especially from the point of view of calibration (identification of parameter values) of the kinematic model of the manipulator and the relative location of the camera and the robot.
7
Content available remote Design and implementation of visual feedback for an active tracking
EN
Active visual tracking is used to direct the attention of the camera to an object and maintain it in the camera's field of view. A steered camera is used to decrease relative motion of the target in the image plane. This leads to better performance of the mean-shift based tracking algorithm, which requires the object tracked in the current and the previous frame to overlap. A classical PID controller and a nonlinear fuzzy controller have been tested in steering the camera head.
8
Content available remote IMM based UKF and IMM based EKF algorithms for tracking highly maneuverable target
EN
This paper aims to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. We consider the case of state estimation in jump Markov nonlinear systems. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose atate and/or measurement models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to compare the results given by an IMM algorithm Extended Kalman filter based (IMM-EKF) versus those given by an IMM algorithm Unscented Kalman Filter based (IMM-UKF) in tracking target assumed to be highly maneuverable.
EN
The problem of the real time estimation of the position and orientation of moving objects for position-based visual servoing control of robotic systems is considered in this paper. A computationally efficient algorithm is proposed based on Kalman filtering of the visual measurements of the position of suitable feature points selected on the target objects. The efficiency of the algorithm is improved by adopting a pre-selection technique of the feature points, based on Binary Space Partitioning (BSP) tree geometric models of the target objects, which takes advantage of the Kalman folter prediction capability. Computer simulations are presented to test the performance of the estimation algorithm in the presence of noise, different types of lens geometric distortion, quantization and calibration errors.
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