Download or read book A Multi task Robot vision System Based on Pose Estimation Algorithms written by Zhipeng Zhang and published by . This book was released on 2019 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vision for Robotics written by Danica Kragic and published by Now Publishers Inc. This book was released on 2009 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robot vision refers to the capability of a robot to visually perceive the environment and use this information for execution of various tasks. Visual feedback has been used extensively for robot navigation and obstacle avoidance. In the recent years, there are also examples that include interaction with people and manipulation of objects. In this paper, we review some of the work that goes beyond of using artificial landmarks and fiducial markers for the purpose of implementing visionbased control in robots. We discuss different application areas, both from the systems perspective and individual problems such as object tracking and recognition.

Download or read book Knowledge Based Vision Guided Robots written by Nick Barnes and published by Physica. This book was released on 2012-12-06 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many robotics researchers consider high-level vision algorithms (computational) too expensive for use in robot guidance. This book introduces the reader to an alternative approach to perception for autonomous, mobile robots. It explores how to apply methods of high-level computer vision and fuzzy logic to the guidance and control of the mobile robot. The book introduces a knowledge-based approach to vision modeling for robot guidance, where advantage is taken of constraints of the robot's physical structure, the tasks it performs, and the environments it works in. This facilitates high-level computer vision algorithms such as object recognition at a speed that is sufficient for real-time navigation. The texts presents algorithms that exploit these constraints at all levels of vision, from image processing to model construction and matching, as well as shape recovery. These algorithms are demonstrated in the navigation of a wheeled mobile robot.

Download or read book Robotic Vision Technologies for Machine Learning and Vision Applications written by Garcia-Rodriguez, Jose and published by IGI Global. This book was released on 2012-12-31 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed. Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Download or read book Control of Multiple Robots Using Vision Sensors written by Miguel Aranda and published by Springer. This book was released on 2017-05-11 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph introduces novel methods for the control and navigation of mobile robots using multiple-1-d-view models obtained from omni-directional cameras. This approach overcomes field-of-view and robustness limitations, simultaneously enhancing accuracy and simplifying application on real platforms. The authors also address coordinated motion tasks for multiple robots, exploring different system architectures, particularly the use of multiple aerial cameras in driving robot formations on the ground. Again, this has benefits of simplicity, scalability and flexibility. Coverage includes details of: a method for visual robot homing based on a memory of omni-directional images; a novel vision-based pose stabilization methodology for non-holonomic ground robots based on sinusoidal-varying control inputs; an algorithm to recover a generic motion between two 1-d views and which does not require a third view; a novel multi-robot setup where multiple camera-carrying unmanned aerial vehicles are used to observe and control a formation of ground mobile robots; and three coordinate-free methods for decentralized mobile robot formation stabilization. The performance of the different methods is evaluated both in simulation and experimentally with real robotic platforms and vision sensors. Control of Multiple Robots Using Vision Sensors will serve both academic researchers studying visual control of single and multiple robots and robotics engineers seeking to design control systems based on visual sensors.

Download or read book Unifying Perspectives in Computational and Robot Vision written by Danica Kragic and published by Springer Science & Business Media. This book was released on 2008-06-06 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a gap between research conducted in the computer vision and robotics communities. This volume discusses contrasting viewpoints of computer vision vs. robotics, and provides current and future challenges discussed from a research perspective.

Download or read book Computer Vision And Robotics In Perioperative Process written by Yi Xu and published by World Scientific. This book was released on 2018-04-10 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable compendium highlights the challenges of perioperative process in hospitals today. It delves into the development of a multi-agent robotic system where a dirty-side robot that sorts instruments returned from a surgical room into different containers for easy scrubbing, a Traybot that navigates the environment and transports the instrument containers to different stations, a clean-side robot that picks up instruments and places them in surgical kits, and an orchestration software architecture that manages the cooperation between different robots.The book discusses the technical details of all the components, from system architecture to the details of the end-effector design. Readers will gain significant knowledge on how such a system was put together.Related Link(s)

Download or read book Visual Perception for Humanoid Robots written by David Israel González Aguirre and published by Springer. This book was released on 2018-09-01 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental questions: What & where is it? To answer these questions using a sensor-to-representation bridge, coordinated processes are conducted to extract and exploit cues matching robot’s mental representations to physical entities. These include sensor & actuator modeling, calibration, filtering, and feature extraction for state estimation. This book discusses the following topics in depth: • Active Sensing: Robust probabilistic methods for optimal, high dynamic range image acquisition are suitable for use with inexpensive cameras. This enables ideal sensing in arbitrary environmental conditions encountered in human-centric spaces. The book quantitatively shows the importance of equipping robots with dependable visual sensing. • Feature Extraction & Recognition: Parameter-free, edge extraction methods based on structural graphs enable the representation of geometric primitives effectively and efficiently. This is done by eccentricity segmentation providing excellent recognition even on noisy & low-resolution images. Stereoscopic vision, Euclidean metric and graph-shape descriptors are shown to be powerful mechanisms for difficult recognition tasks. • Global Self-Localization & Depth Uncertainty Learning: Simultaneous feature matching for global localization and 6D self-pose estimation are addressed by a novel geometric and probabilistic concept using intersection of Gaussian spheres. The path from intuition to the closed-form optimal solution determining the robot location is described, including a supervised learning method for uncertainty depth modeling based on extensive ground-truth training data from a motion capture system. The methods and experiments are presented in self-contained chapters with comparisons and the state of the art. The algorithms were implemented and empirically evaluated on two humanoid robots: ARMAR III-A & B. The excellent robustness, performance and derived results received an award at the IEEE conference on humanoid robots and the contributions have been utilized for numerous visual manipulation tasks with demonstration at distinguished venues such as ICRA, CeBIT, IAS, and Automatica.

Download or read book Active Sensor Planning for Multiview Vision Tasks written by Shengyong Chen and published by Springer Science & Business Media. This book was released on 2008-01-23 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book explores the important issues in studying for active visual perception. The book’s eleven chapters draw on recent important work in robot vision over ten years, particularly in the use of new concepts. Implementation examples are provided with theoretical methods for testing in a real robot system. With these optimal sensor planning strategies, this book will give the robot vision system the adaptability needed in many practical applications.

Download or read book Multi View Geometry Based Visual Perception and Control of Robotic Systems written by Jian Chen and published by CRC Press. This book was released on 2018-06-14 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes visual perception and control methods for robotic systems that need to interact with the environment. Multiple view geometry is utilized to extract low-dimensional geometric information from abundant and high-dimensional image information, making it convenient to develop general solutions for robot perception and control tasks. In this book, multiple view geometry is used for geometric modeling and scaled pose estimation. Then Lyapunov methods are applied to design stabilizing control laws in the presence of model uncertainties and multiple constraints.

Download or read book Vision Based Identification and Force Control of Industrial Robots written by Abdullah Aamir Hayat and published by Springer Nature. This book was released on 2022-03-21 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on end-to-end robotic applications using vision and control algorithms, exposing its readers to design innovative solutions towards sensors-guided robotic bin-picking and assembly in an unstructured environment. The use of sensor fusion is demonstrated through a bin-picking task of texture-less cylindrical objects. The system identification techniques are also discussed for obtaining precise kinematic and dynamic parameters of an industrial robot which facilitates the control schemes to perform pick-and-place tasks autonomously without any interference from the user. The uniqueness of this book lies in a judicious balance between theory and technology within the context of industrial application. Therefore, it will be valuable to researchers working in the area of vision- and force control- based robotics, as well as beginners in this inter-disciplinary area, as it deals with the basics and technologically advanced research strategies.

Download or read book Robot Vision written by Ales Ude and published by BoD – Books on Demand. This book was released on 2010-03-01 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of robot vision is to enable robots to perceive the external world in order to perform a large range of tasks such as navigation, visual servoing for object tracking and manipulation, object recognition and categorization, surveillance, and higher-level decision-making. Among different perceptual modalities, vision is arguably the most important one. It is therefore an essential building block of a cognitive robot. This book presents a snapshot of the wide variety of work in robot vision that is currently going on in different parts of the world.

Download or read book Robotic Vision written by Peter Corke and published by Springer Nature. This book was released on 2021-10-15 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers a tutorial introduction to robotics and Computer Vision which is light and easy to absorb. The practice of robotic vision involves the application of computational algorithms to data. Over the fairly recent history of the fields of robotics and computer vision a very large body of algorithms has been developed. However this body of knowledge is something of a barrier for anybody entering the field, or even looking to see if they want to enter the field — What is the right algorithm for a particular problem?, and importantly: How can I try it out without spending days coding and debugging it from the original research papers? The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provide a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used —instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals light and color, camera modelling, image processing, feature extraction and multi-view geometry, and bring it all together in a visual servo system. “An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished Oussama Khatib, Stanford

Download or read book Perception for Control and Control for Perception of Vision based Autonomous Aerial Robots written by Eric Cristofalo and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The mission of this thesis is to develop visual perception and feedback control algorithms for autonomous aerial robots that are equipped with an onboard camera. We introduce light-weight algorithms that parse images from the robot's camera directly into feedback signals for control laws that improve perception quality. We emphasize the co-design, analysis, and implementation of the perception, planning, and control tasks to ensure that the entire autonomy pipeline is suitable for aerial robots with real-world constraints. The methods presented in this thesis further leverage perception for control and control for perception: the former uses perception to inform the robot how to act while the later uses robotic control to improve the robot's perception of the world. Perception in this work refers to the processing of raw sensor measurements and the estimation of state values while control refers to the planning of useful robot motions and control inputs based on these state estimates. The major capability that we enable is a robot's ability to sense this unmeasured scene geometry as well as the three-dimensional (3D) robot pose from images acquired by its onboard camera. Our algorithms specifically enable a UAV with an onboard camera to use control to reconstruct the 3D geometry of its environment in a both sparse sense and a dense sense, estimate its own global pose with respect to the environment, and estimate the relative poses of other UAVs and dynamic objects of interest in the scene. All methods are implemented on real robots with real-world sensory, power, communication, and computation constraints to demonstrate the need for tightly-coupled, fast perception and control in robot autonomy. Depth estimation at specific pixel locations is often considered to be a perception-specific task for a single robot. We instead control the robot to steer a sensor to improve this depth estimation. First, we develop an active perception controller that maneuvers a quadrotor with a downward facing camera according to the gradient of maximum uncertainty reduction for a sparse subset of image features. This allows us to actively build a 3D point cloud representation of the scene quickly and thus enabling fast situational awareness for the aerial robot. Our method reduces uncertainty more quickly than state-of-the-art approaches for approximately an order of magnitude less computation time. Second, we autonomously control the focus mechanism on a camera lens to build metric-scale, dense depth maps that are suitable for robotic localization and navigation. Compared to the depth data from an off-the-shelf RGB-D sensor (Microsoft Kinect), our Depth-from-Focus method recovers the depth for 88% of the pixels with no RGB-D measurements in near-field regime (0.0 - 0.5 meters), making it a suitable complimentary sensor for RGB-D. We demonstrate dense sensing on a ground robot localization application and with AirSim, an advanced aerial robot simulator. We then consider applications where groups of aerial robots with monocular cameras seek to estimate their pose, or position and orientation, in the environment. Examples include formation control, target tracking, drone racing, and pose graph optimization. Here, we employ ideas from control theory to perform the pose estimation. We first propose the tight-coupling of pairwise relative pose estimation with cooperative control methods for distributed formation control using quadrotors with downward facing cameras, target tracking in a heterogenous robot system, and relative pose estimation for competitive drone racing. We experimentally validate all methods with real-time perception and control implementations. Finally, we develop a distributed pose graph optimization method for networks of robots with noisy relative pose measurements. Unlike existing pose graph optimization methods, our method is inspired by control theoretic approaches to distributed formation control. We leverage tools from Lyapunov theory and multi-agent consensus to derive a relative pose estimation algorithm with provable performance guarantees. Our method also reaches consensus 13x faster than a state-of-the-art centralized strategy and reaches solutions that are approximately 6x more accurate than decentralized pose estimation methods. While the computation times between our method and the benchmarch distributed method are similar for small networks, ours outperforms the benchmark by a factor of 100 on networks with large numbers of robots (> 1000). Our approach is easy to implement and fast, making it suitable for a distributed backend in a SLAM application. Our methods will ultimately allow micro aerial vehicles to perform more complicated tasks. Our focus on tightly-coupled perception and control leads to algorithms that are streamlined for real aerial robots with real constraints. These robots will be more flexible for applications including infrastructure inspection, automated farming, and cinematography. Our methods will also enable more robot-to-robot collaboration since we present effective ways to estimate the relative pose between them. Multi-robot systems will be an important part of the robotic future as they are robust to the failure of individual robots and allow complex computation to be distributed amongst the agents. Most of all, our methods allow robots to be more self sufficient by utilizing their onboard camera and by accurately estimating the world's structure. We believe these methods will enable aerial robots to better understand our 3D world.

Download or read book Active Robot Vision Camera Heads Model Based Navigation And Reactive Control written by Kevin Bowyer and published by World Scientific. This book was released on 1993-05-13 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Editorial (H I Christensen et al.)The Harvard Binocular Head (N J Ferrier & J J Clark)Heads, Eyes, and Head-Eye Systems (K Pahlavan & J-O Eklundh)Design and Performance of TRISH, a Binocular Robot Head with Torsional Eye Movements (E Milios et al.)A Low-Cost Robot Camera Head (H I Christensen)The Surrey Attentive Robot Vision System (J R G Pretlove & G A Parker)Layered Control of a Binocular Camera Head (J L Crowley et al.)SAVIC: A Simulation, Visualization and Interactive Control Environment for Mobile Robots (C Chen & M M Trivedi)Simulation and Expectation in Sensor-Based Systems (Y Roth & R Jain)Active Avoidance: Escape and Dodging Behaviors for Reactive Control (R C Arkin et al.) Readership: Engineers and computer scientists. keywords:Active Vision;Robot Vision;Computer Vision;Model-Based Vision;Robot Navigation;Reactive Control;Robot Motion Planning;Knowledge-Based Vision;Robotics

Download or read book Intelligent active vision systems for robots written by Erik Valdemar Cuevas Jiménez and published by Cuvillier Verlag. This book was released on 2007-01-08 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, an active vision system is developed which is based on image strategy. The image based control structure uses the optical flow algorithm for motion detection of an object in a visual scene. Because the optical flow is very sensitive to changes in illumination or to the quality of the video, it was necessary to use median filtering and erosion and dilatation morphological operations for the decrease of erroneous blobs residing in individual frames. Since the image coordinates of the object are subjected to noise, the Kalman filtering technique is adopted for robust estimation. A fuzzy controller based on the fuzzy condensed algorithm allows real time work for each captured frame. Finally, the proposed active vision system has been simulated in the development/simulation environment Matlab/Simulink.

Download or read book Collaborative Engineering written by Ali K. Kamrani and published by Springer Science & Business Media. This book was released on 2008-07-08 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This superb study offers insights into the methods and techniques that enable the implementation of a Collaborative Engineering concept on product design. It does so by integrating capabilities for intelligent information support and group decision-making, utilizing a common enterprise network model and knowledge interface through shared ontologies. The book is also a collection of the latest applied methods and technology from selected experts in this area.