132 research outputs found

    Visual Servoing

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    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

    Workshop on "Control issues in the micro / nano - world".

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    International audienceDuring the last decade, the need of systems with micro/nanometers accuracy and fast dynamics has been growing rapidly. Such systems occur in applications including 1) micromanipulation of biological cells, 2) micrassembly of MEMS/MOEMS, 3) micro/nanosensors for environmental monitoring, 4) nanometer resolution imaging and metrology (AFM and SEM). The scale and requirement of such systems present a number of challenges to the control system design that will be addressed in this workshop. Working in the micro/nano-world involves displacements from nanometers to tens of microns. Because of this precision requirement, environmental conditions such as temperature, humidity, vibration, could generate noise and disturbance that are in the same range as the displacements of interest. The so-called smart materials, e.g., piezoceramics, magnetostrictive, shape memory, electroactive polymer, have been used for actuation or sensing in the micro/nano-world. They allow high resolution positioning as compared to hinges based systems. However, these materials exhibit hysteresis nonlinearity, and in the case of piezoelectric materials, drifts (called creep) in response to constant inputs In the case of oscillating micro/nano-structures (cantilever, tube), these nonlinearities and vibrations strongly decrease their performances. Many MEMS and NEMS applications involve gripping, feeding, or sorting, operations, where sensor feedback is necessary for their execution. Sensors that are readily available, e.g., interferometer, triangulation laser, and machine vision, are bulky and expensive. Sensors that are compact in size and convenient for packaging, e.g., strain gage, piezoceramic charge sensor, etc., have limited performance or robustness. To account for these difficulties, new control oriented techniques are emerging, such as[d the combination of two or more ‘packageable' sensors , the use of feedforward control technique which does not require sensors, and the use of robust controllers which account the sensor characteristics. The aim of this workshop is to provide a forum for specialists to present and overview the different approaches of control system design for the micro/nano-world and to initiate collaborations and joint projects

    Industrial Robotics

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    This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

    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

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    学位の種別:課程博士University of Tokyo(東京大学

    Robust Position-based Visual Servoing of Industrial Robots

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    Recently, the researchers have tried to use dynamic pose correction methods to improve the accuracy of industrial robots. The application of dynamic path tracking aims at adjusting the end-effector’s pose by using a photogrammetry sensor and eye-to-hand PBVS scheme. In this study, the research aims to enhance the accuracy of industrial robot by designing a chattering-free digital sliding mode controller integrated with a novel adaptive robust Kalman filter (ARKF) validated on Puma 560 model on simulation. This study includes Gaussian noise generation, pose estimation, design of adaptive robust Kalman filter, and design of chattering-free sliding mode controller. The designed control strategy has been validated and compared with other control strategies in Matlab 2018a Simulink on a 64bits PC computer. The main contributions of the research work are summarized as follows. First, the noise removal in the pose estimation is carried out by the novel ARKF. The proposed ARKF deals with experimental noise generated from photogrammetry observation sensor C-track 780. It exploits the advantages of adaptive estimation method for states noise covariance (Q), least square identification for measurement noise covariance (R) and a robust mechanism for state variables error covariance (P). The Gaussian noise generation is based on the collected data from the C-track when the robot is in a stationary status. A novel method for estimating covariance matrix R considering both effects of the velocity and pose is suggested. Next, a robust PBVS approach for industrial robots based on fast discrete sliding mode controller (FDSMC) and ARKF is proposed. The FDSMC takes advantage of a nonlinear reaching law which results in faster and more accurate trajectory tracking compared to standard DSMC. Substituting the switching function with a continuous nonlinear reaching law leads to a continuous output and thus eliminating the chattering. Additionally, the sliding surface dynamics is considered to be a nonlinear one, which results in increasing the convergence speed and accuracy. Finally, the analysis techniques related to various types of sliding mode controller have been used for comparison. Also, the kinematic and dynamic models with revolutionary joints for Puma 560 are built for simulation validation. Based on the computed indicators results, it is proven that after tuning the parameters of designed controller, the chattering-free FDSMC integrated with ARKF can essentially reduce the effect of uncertainties on robot dynamic model and improve the tracking accuracy of the 6 degree-of-freedom (DOF) robot

    Grasping, Perching, And Visual Servoing For Micro Aerial Vehicles

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    Micro Aerial Vehicles (MAVs) have seen a dramatic growth in the consumer market because of their ability to provide new vantage points for aerial photography and videography. However, there is little consideration for physical interaction with the environment surrounding them. Onboard manipulators are absent, and onboard perception, if existent, is used to avoid obstacles and maintain a minimum distance from them. There are many applications, however, which would benefit greatly from aerial manipulation or flight in close proximity to structures. This work is focused on facilitating these types of close interactions between quadrotors and surrounding objects. We first explore high-speed grasping, enabling a quadrotor to quickly grasp an object while moving at a high relative velocity. Next, we discuss planning and control strategies, empowering a quadrotor to perch on vertical surfaces using a downward-facing gripper. Then, we demonstrate that such interactions can be achieved using only onboard sensors by incorporating vision-based control and vision-based planning. In particular, we show how a quadrotor can use a single camera and an Inertial Measurement Unit (IMU) to perch on a cylinder. Finally, we generalize our approach to consider objects in motion, and we present relative pose estimation and planning, enabling tracking of a moving sphere using only an onboard camera and IMU

    High Resolution Vision-Based Servomechanism Using a Dynamic Target with Application to CNC Machines

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    This dissertation introduces a novel three dimensional vision-based servomechanism with application to real time position control for manufacturing equipment, such as Computer Numerical Control (CNC) machine tools. The proposed system directly observes the multi-dimensional position of a point on the moving tool relative to a fixed ground, thus bypassing the inaccurate kinematic model normally used to convert axis sensor-readings into an estimate of the tool position. A charge-coupled device (CCD camera) is used as the position transducer, which directly measures the current position error of the tool referenced to an absolute coordinate system. Due to the direct-sensing nature of the transducer no geometric error compensation is required. Two new signal processing algorithms, based on a recursive Newton-Raphson optimization routine, are developed to process the input data collected through digital imaging. The algorithms allow simultaneous high-precision position and orientation estimation from single readings. The desired displacement command of the tool in a planar environment is emulated, in one end of the kinematic chain, by an active element or active target pattern on a liquid-crystal display (LCD). On the other end of the kinematic chain the digital camera observes the active target and provides visual feedback information utilized for position control of the tool. Implementation is carried out on an XYθZ stage, which is position with high resolution. The introduction of the camera into the control loop yields a visual servo architecture; the dynamic problems and stability assessment of which are analyzed in depth for the case study of the single CAM- single image processing thread-configuration. Finally, two new command generation protocols are explained for full implementation of the proposed structure in real-time control applications. Command issuing resolutions do not depend upon the size of the smallest element of the grid/display being imaged, but can instead be determined in accordance with the sensor\u27s resolution

    Robotic contour tracking with adaptive feedforward control by fuzzy online tuning

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    Industrial robots have great importance in manufacturing. Typical uses of the robots are welding, painting, deburring, grinding, polishing and shape recovery. Most of these tasks such as grinding, deburring need force control to achieve high performance. These tasks involve contour following. Contour following is a challenging task because in many of applications the geometry physical of the targeted contour are unknown. In addition to that, achieving tasks as polishing, grinding and deburring requires small force and velocity tracking errors. In order to accomplish these tasks, disturbances have to be taken account. In this thesis the aim is to achieve contour tracking with using fuzzy online tuning. The fuzzy method is proposed in this thesis to adjust a feedforward force control parameter. In this technique, the varying feedforward control parameter compensates for disturbance effects. The method employs the chattering of control signal and the normal force and tangential velocity errors to adjust the control term. Simulations with the model of a direct drive planar elbow manipulator are used to last proposed technique
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