Uncalibrated eye-to-hand visual servoing using inverse fuzzy models

(c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.A new uncalibrated eye-to-hand visual servoing based on inverse fuzzy modeling is proposed in this paper. In classical visual servoing, the Jacobian plays a decisive role in the convergence of the controller, as its analytical model depends on the selected image features. This Jacobian must also be inverted online. Fuzzy modeling is applied to obtain an inverse model of the mapping between image feature variations and joint velocities. This approach is independent from the robot's kinematic model or camera calibration and also avoids the necessity of inverting the Jacobian online. An inverse model is identified for the robot workspace, using measurement data of a robotic manipulator. This inverse model is directly used as a controller. The inverse fuzzy control scheme is applied to a robotic manipulator performing visual servoing for random positioning in the robot workspace. The obtained experimental results show the effectiveness of the proposed control scheme. The fuzzy controller can position the robotic manipulator at any point in the workspace with better accuracy than the classic visual servoing approach.info:eu-repo/semantics/publishedVersio

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

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

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Ultrasound based navigation and control for orthopaedic robot surgery

Thesis approved in public session to obtain the PhD Degree in Mechanical Engineering. Universidade de Lisboa. Instituto Superior TécnicoA Robótica cirúrgica é uma área em expansão, contribuindo para o aumento da precisão e exatidão dos procedimentos cirúrgicos, além de produzir resultados mais confiáveis e reprodutíveis, minimizando a invasividade, reduzindo as complicações e melhorando a segurança dos pacientes, comparativamente com as técnicas convencionais. A navegação dentro da sala de operações é primordial para o sucesso dos sistemas robóticos. Neste contexto é proposto um novo sistema de navegação, usado na malha de controlo, de um sistema robótico co-manipulado, dedesenvolvido para auxiliar os cirurgiões ortopédicos. Embora possa ter outras aplicações, o sistema foi desenvolvido para realizar um furo na cabeça do fémur, necessário ao implante do fio guia na cirurgia de substituição parcial da anca. Durante a cirurgia, a posição e orientação do osso é obtida através de um processo de registo entre as imagens de US adquiridas em tempo real e o modelo CT do fémur, previamente carregado no pré-operatório. Contrariamente aos sistemas cirúrgicos atuais, não usa nenhum tipo de implante no osso para localizar o fémur, mas sim marcadores passivos colocados na sonda e no robô, e um sistema de medição óptico para medir as suas posições 3D. Os testes experimentais de validação foram realizados num phantom de um fémur humano.Abstract: Surgical Robotics is an expanding area, contributing to the increased precision and accuracy of surgical procedures, besides producing more reliable and reproducible results, minimizing the invasiveness, reducing complications and improving patient safety, compared with conventional techniques. Navigation within the operating room is fundamental to the success of robotic systems. In this context a new navigation system, used in the control loop, to co-manipulate a robotic system developed to assist orthopaedic surgeons, is proposed. Although it may have other applications, the system is designed to perform a hole in the femur head, necessary to implant the initial guide wire used in Hip Resurfacing surgery. During the surgery, the bone position and orientation is obtained through a registration process between a set of US images acquired in real time and the CT femur model, preloaded pre-operatively. Contrary to current surgical systems, it does not use any type of implant in the bone, to localize the femur, but passive markers, of an optical measurement system, placed on the probe and the robot to measure their 3D poses. Experimental validation tests were performed on a human’s femur phantom, validating the proposed system

Adaptive Finite-Time Model Estimation and Control for Manipulator Visual Servoing using Sliding Mode Control and Neural Networks

The image-based visual servoing without models of system is challenging since it is hard to fetch an accurate estimation of hand-eye relationship via merely visual measurement. Whereas, the accuracy of estimated hand-eye relationship expressed in local linear format with Jacobian matrix is important to whole system's performance. In this article, we proposed a finite-time controller as well as a Jacobian matrix estimator in a combination of online and offline way. The local linear formulation is formulated first. Then, we use a combination of online and offline method to boost the estimation of the highly coupled and nonlinear hand-eye relationship with data collected via depth camera. A neural network (NN) is pre-trained to give a relative reasonable initial estimation of Jacobian matrix. Then, an online updating method is carried out to modify the offline trained NN for a more accurate estimation. Moreover, sliding mode control algorithm is introduced to realize a finite-time controller. Compared with previous methods, our algorithm possesses better convergence speed. The proposed estimator possesses excellent performance in the accuracy of initial estimation and powerful tracking capabilities for time-varying estimation for Jacobian matrix compared with other data-driven estimators. The proposed scheme acquires the combination of neural network and finite-time control effect which drives a faster convergence speed compared with the exponentially converge ones. Another main feature of our algorithm is that the state signals in system is proved to be semi-global practical finite-time stable. Several experiments are carried out to validate proposed algorithm's performance.Comment: 24 pages, 10 figure

Model free visual servoing in macro and micro domain robotic applications

This thesis explores model free visual servoing algorithms by experimentally evaluating their performances for various tasks performed both in macro and micro domains. Model free or so called uncalibrated visual servoing does not need the system (vision system + robotic system) calibration and the model of the observed scene, since it provides an online estimation of the composite (image + robot) Jacobian. It is robust to parameter changes and disturbances. A model free visual servoing scheme is tested on a 7 DOF Mitsubishi PA10 robotic arm and on a microassembly workstation which is developed in our lab. In macro domain, a new approach for planar shape alignment is presented. The alignment task is performed based on bitangent points which are acquired using convex-hull of a curve. Both calibrated and uncalibrated visual servoing schemes are employed and compared. Furthermore, model free visual servoing is used for various trajectory following tasks such as square, circle, sine etc. and these reference trajectories are generated by a linear interpolator which produces midway targets along them. Model free visual servoing can provide more exibility in microsystems, since the calibration of the optical system is a tedious and error prone process, and recalibration is required at each focusing level of the optical system. Therefore, micropositioning and three di erent trajectory following tasks are also performed in micro world. Experimental results validate the utility of model free visual servoing algorithms in both domains

相対座標における高速視覚フィードバックに基づくダイナミックコンペンセーション

学位の種別:課程博士University of Tokyo(東京大学

Adaptive Neuro-Filtering Based Visual Servo Control of a Robotic Manipulator

This paper focuses on the solutions to flexibly regulate robotic by vision. A new visual servoing technique based on the Kalman filtering (KF) combined neural network (NN) is developed, which need not have any calibration parameters of robotic system. The statistic knowledge of the system noise and observation noise are first given by Gaussian white noise sequences, the nonlinear mapping between robotic vision and motor spaces are then on-line identified using standard Kalman recursive equations. In real robotic workshops, the perfect statistic knowledge of the noise is not easy to be derived, thus an adaptive neuro-filtering approach based on KF is also studied for mapping on-line estimation in this paper. The Kalman recursive equations are improved by a feedforward NN, in which the neural estimator dynamic adjusts its weights to minimize estimation error of robotic vision-motor mapping, without the knowledge of noise variances. Finally, the proposed visual servoing based on adaptive neuro-filtering has been successfully implemented in robotic pose regulation, and the experimental results demonstrate its validity and practicality for a six-degree-of-freedom (DOF) robotic system which the hand-eye without calibrated