Vision For Robot Navigation Localization And Object Recognition
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Vision For Robot Navigation Localization And Object Recognition
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Author : Jason Meltzer
language : en
Publisher:
Release Date : 2010
Vision For Robot Navigation Localization And Object Recognition written by Jason Meltzer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
New Development In Robot Vision
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Author : Yu Sun
language : en
Publisher: Springer
Release Date : 2014-09-26
New Development In Robot Vision written by Yu Sun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-26 with Technology & Engineering categories.
The field of robotic vision has advanced dramatically recently with the development of new range sensors. Tremendous progress has been made resulting in significant impact on areas such as robotic navigation, scene/environment understanding, and visual learning. This edited book provides a solid and diversified reference source for some of the most recent important advancements in the field of robotic vision. The book starts with articles that describe new techniques to understand scenes from 2D/3D data such as estimation of planar structures, recognition of multiple objects in the scene using different kinds of features as well as their spatial and semantic relationships, generation of 3D object models, approach to recognize partially occluded objects, etc. Novel techniques are introduced to improve 3D perception accuracy with other sensors such as a gyroscope, positioning accuracy with a visual servoing based alignment strategy for microassembly, and increasing object recognition reliability using related manipulation motion models. For autonomous robot navigation, different vision-based localization and tracking strategies and algorithms are discussed. New approaches using probabilistic analysis for robot navigation, online learning of vision-based robot control, and 3D motion estimation via intensity differences from a monocular camera are described. This collection will be beneficial to graduate students, researchers, and professionals working in the area of robotic vision.
Machine Learning Based Natural Scene Recognition For Mobile Robot Localization In An Unknown Environment
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Author : Xiaochun Wang
language : en
Publisher: Springer
Release Date : 2019-08-12
Machine Learning Based Natural Scene Recognition For Mobile Robot Localization In An Unknown Environment written by Xiaochun Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-12 with Technology & Engineering categories.
This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.
Vision Based Autonomous Robot Navigation
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Author : Amitava Chatterjee
language : en
Publisher: Springer
Release Date : 2012-10-13
Vision Based Autonomous Robot Navigation written by Amitava Chatterjee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-13 with Technology & Engineering categories.
This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.
Bearing Only Simultaneous Localization And Mapping For Vision Based Mobile Robots
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Author : Henry Huang
language : en
Publisher:
Release Date : 2007
Bearing Only Simultaneous Localization And Mapping For Vision Based Mobile Robots written by Henry Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
In this chapter, we proposed a vision-based approach to bearing-only SLAM in a 2dimensional space. We assumed the environment contained several visually distinguishable landmarks. This approach is inspired from techniques used in stereo vision and Structure From Motion. Our landmark initialization method relies solely on the bearing measurements from a single camera. This method does not require information from an odometer or a range sensor. All the object positions can be estimated in a landmark-based frame. The trade-off is that this method requires the robot to be able to move in a straight line for a short while to initialize the landmarks. The proposed method is particularly accurate and useful when the robot can guide itself in a straight line by visually locking on static objects. Since the method does not rely on odometry and range information, the induced map is up to a scale factor only. In our method, the distance L1 - L 2 of two landmarks is taken as the measurement unit of the map. The selection of L1 and L 2 is critical for the accuracy of.
Robot Localization And Map Building
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Author : Hanafiah Yussof
language : en
Publisher: IntechOpen
Release Date : 2010-03-01
Robot Localization And Map Building written by Hanafiah Yussof and has been published by IntechOpen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-01 with Computers categories.
Localization and mapping are the essence of successful navigation in mobile platform technology. Localization is a fundamental task in order to achieve high levels of autonomy in robot navigation and robustness in vehicle positioning. Robot localization and mapping is commonly related to cartography, combining science, technique and computation to build a trajectory map that reality can be modelled in ways that communicate spatial information effectively. This book describes comprehensive introduction, theories and applications related to localization, positioning and map building in mobile robot and autonomous vehicle platforms. It is organized in twenty seven chapters. Each chapter is rich with different degrees of details and approaches, supported by unique and actual resources that make it possible for readers to explore and learn the up to date knowledge in robot navigation technology. Understanding the theory and principles described in this book requires a multidisciplinary background of robotics, nonlinear system, sensor network, network engineering, computer science, physics, etc.
Visual Perception For Humanoid Robots
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Author : David Israel González Aguirre
language : en
Publisher: Springer
Release Date : 2018-09-01
Visual Perception For Humanoid Robots written by David Israel González Aguirre and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-01 with Technology & Engineering categories.
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.
Machine Vision And Navigation
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Author : Oleg Sergiyenko
language : en
Publisher: Springer Nature
Release Date : 2019-09-30
Machine Vision And Navigation written by Oleg Sergiyenko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-30 with Technology & Engineering categories.
This book presents a variety of perspectives on vision-based applications. These contributions are focused on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms and vision systems. The authors focus on applications of unmanned aerial vehicles, autonomous and mobile robots, industrial inspection applications and structural health monitoring. Recent advanced research in measurement and others areas where 3D & 2D machine vision and machine control play an important role, as well as surveys and reviews about vision-based applications. These topics are of interest to readers from diverse areas, including electrical, electronics and computer engineering, technologists, students and non-specialist readers. • Presents current research in image and signal sensors, methods, and 3D & 2D technologies in vision-based theories and applications; • Discusses applications such as daily use devices including robotics, detection, tracking and stereoscopic vision systems, pose estimation, avoidance of objects, control and data exchange for navigation, and aerial imagery processing; • Includes research contributions in scientific, industrial, and civil applications.
Three Dimensional Object Recognition From Range Images
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Author : Minsoo Suk
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Three Dimensional Object Recognition From Range Images written by Minsoo Suk and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. T08iyasu L. Kunii PREFACE The primary aim of this book is to present a coherent and self-contained de scription of recent advances in three-dimensional object recognition from range images. Three-dimensional object recognition concerns recognition and localiza tion of objects of interest in a scene from input images. This problem is one of both theoretical and practical importance. On the theoretical side, it is an ideal vehicle for the study of the general area of computer vision since it deals with several important issues encountered in computer vision-for example, issues such as feature extraction, acquisition, representation and proper use of knowl edge, employment of efficient control strategies, coupling numerical and symbolic computations, and parallel implementation of algorithms. On the practical side, it has a wide range of applications in areas such as robot vision, autonomous navigation, automated inspection of industrial parts, and automated assembly.
Unifying Perspectives In Computational And Robot Vision
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Author : Danica Kragic
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-06
Unifying Perspectives In Computational And Robot Vision written by Danica Kragic and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-06 with Computers categories.
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.