Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Visual Perception And Robotic Manipulation
Download Visual Perception And Robotic Manipulation full books in PDF, epub, and Kindle. Read online Visual Perception And Robotic Manipulation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Visual Perception and Robotic Manipulation by : Geoffrey Taylor
Download or read book Visual Perception and Robotic Manipulation written by Geoffrey Taylor and published by Springer. This book was released on 2008-08-18 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book moves toward the realization of domestic robots by presenting an integrated view of computer vision and robotics, covering fundamental topics including optimal sensor design, visual servo-ing, 3D object modelling and recognition, and multi-cue tracking, emphasizing robustness throughout. Covering theory and implementation, experimental results and comprehensive multimedia support including video clips, VRML data, C++ code and lecture slides, this book is a practical reference for roboticists and a valuable teaching resource.
Book Synopsis Visual Perception for Manipulation and Imitation in Humanoid Robots by : Pedram Azad
Download or read book Visual Perception for Manipulation and Imitation in Humanoid Robots written by Pedram Azad and published by Springer Science & Business Media. This book was released on 2009-11-19 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with visual perception in robots and its applications to manipulation and imitation, this monograph focuses on stereo-based methods and systems for object recognition and 6 DoF pose estimation as well as for marker-less human motion capture.
Book Synopsis Cognitive Reasoning for Compliant Robot Manipulation by : Daniel Sebastian Leidner
Download or read book Cognitive Reasoning for Compliant Robot Manipulation written by Daniel Sebastian Leidner and published by Springer. This book was released on 2018-12-08 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to achieve human-like performance, this book covers the four steps of reasoning a robot must provide in the concept of intelligent physical compliance: to represent, plan, execute, and interpret compliant manipulation tasks. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. It is investigated how symbolic task descriptions can be translated into meaningful robot commands.Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands the humanoid robot Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment
Book Synopsis Vision-based Perception For Autonomous Robotic Manipulation by : Dinh-Cuong Hoang
Download or read book Vision-based Perception For Autonomous Robotic Manipulation written by Dinh-Cuong Hoang and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning for Robot Perception and Cognition by : Alexandros Iosifidis
Download or read book Deep Learning for Robot Perception and Cognition written by Alexandros Iosifidis and published by Academic Press. This book was released on 2022-02-04 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. Presents deep learning principles and methodologies Explains the principles of applying end-to-end learning in robotics applications Presents how to design and train deep learning models Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more Uses robotic simulation environments for training deep learning models Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
Book Synopsis Multi-View Geometry Based Visual Perception and Control of Robotic Systems by : Jian Chen
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.
Book Synopsis Approaches to Probabilistic Model Learning for Mobile Manipulation Robots by : Jürgen Sturm
Download or read book Approaches to Probabilistic Model Learning for Mobile Manipulation Robots written by Jürgen Sturm and published by Springer. This book was released on 2013-12-12 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents techniques that enable mobile manipulation robots to autonomously adapt to new situations. Covers kinematic modeling and learning; self-calibration; tactile sensing and object recognition; imitation learning and programming by demonstration.
Book Synopsis Visual Perception for Humanoid Robots by : David Israel González Aguirre
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.
Book Synopsis Aerial Robotic Manipulation by : Anibal Ollero
Download or read book Aerial Robotic Manipulation written by Anibal Ollero and published by Springer. This book was released on 2019-06-27 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerial robotic manipulation integrates concepts and technologies coming from unmanned aerial systems and robotics manipulation. It includes not only kinematic, dynamics, aerodynamics and control but also perception, planning, design aspects, mechatronics and cooperation between several aerial robotics manipulators. All these topics are considered in this book in which the main research and development approaches in aerial robotic manipulation are presented, including the description of relevant systems. In addition of the research aspects, the book also includes the deployment of real systems both indoors and outdoors, which is a relevant characteristic of the book because most results of aerial robotic manipulation have been validated only indoor using motion tracking systems. Moreover, the book presents two relevant applications: structure assembly and inspection and maintenance, which has started to be applied in the industry. The Chapters of the book will present results of two main European Robotics Projects in aerial robotics manipulation: FP7 ARCAS and H2020 AEROARMS. FP7 ARCAS defined the basic concepts on aerial robotic manipulation, including cooperative manipulation. The H2020 AEROARMS on aerial robot with multiple arms and advanced manipulation capabilities for inspection and maintenance has two general objectives: (1) development of advanced aerial robotic manipulation methods and technologies, including manipulation with dual arms and multi-directional thrusters aerial platforms; and (2) application to the inspection and maintenance.
Book Synopsis Multi-view Geometry Based Visual Perception and Control of Robotic Systems by : Jian Chen
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 with total page 342 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.
Book Synopsis Vision for Robotics by : Danica Kragic
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.
Book Synopsis Dense Visual Learning for Robot Manipulation by : Peter Raymond Florence
Download or read book Dense Visual Learning for Robot Manipulation written by Peter Raymond Florence and published by . This book was released on 2020 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: We would like to have highly useful robots which can richly perceive their world, semantically distinguish its fine details, and physically interact with it sufficiently for useful robotic manipulation. This is hard to achieve with previous methods: prior work has not equipped robots with the scalable ability to understand the dense visual state of their varied environments. The limitations have both been in the state representations used, and how to acquire them without significant human labeling effort. In this thesis we present work that leverages self-supervision, particularly via a mix of geometrical computer vision, deep visual learning, and robotic systems, to scalably produce dense visual inferences of the world state. These methods either enable robots to teach themselves dense visual models without human supervision, or they act as a large multiplying factor on the value of information provided by humans. Specifically, we develop a pipeline for providing ground truth labels of visual data in cluttered and multi-object scenes, we introduce the novel application of dense visual object descriptors to robotic manipulation and provide a fully robot-supervised pipeline to acquire them, and we leverage this dense visual understanding to efficiently learn new manipulation skills through imitation. With real robot hardware we demonstrate contact-rich tasks manipulating household objects, including generalizing across a class of objects, manipulating deformable objects, and manipulating a textureless symmetrical object, all with closed-loop, real-time vision-based manipulation policies.
Book Synopsis Active Perception and Robot Vision by : Arun K. Sood
Download or read book Active Perception and Robot Vision written by Arun K. Sood and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 747 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent robotics has become the focus of extensive research activity. This effort has been motivated by the wide variety of applications that can benefit from the developments. These applications often involve mobile robots, multiple robots working and interacting in the same work area, and operations in hazardous environments like nuclear power plants. Applications in the consumer and service sectors are also attracting interest. These applications have highlighted the importance of performance, safety, reliability, and fault tolerance. This volume is a selection of papers from a NATO Advanced Study Institute held in July 1989 with a focus on active perception and robot vision. The papers deal with such issues as motion understanding, 3-D data analysis, error minimization, object and environment modeling, object detection and recognition, parallel and real-time vision, and data fusion. The paradigm underlying the papers is that robotic systems require repeated and hierarchical application of the perception-planning-action cycle. The primary focus of the papers is the perception part of the cycle. Issues related to complete implementations are also discussed.
Book Synopsis Visuo-tactile Perception for Dexterous Robotic Manipulation by : Maria Bauza Villalonga
Download or read book Visuo-tactile Perception for Dexterous Robotic Manipulation written by Maria Bauza Villalonga and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we develop visuo-tactile perception to enable general and precise robotic manipulation. In particular, we want to study how to effectively process visual and tactile information to allow robots to expand their capabilities while remaining accurate and reliable. We begin our work by focusing on developing tools for tactile perception. For the task of grasping, we use tactile observations to assess and improve grasp stability. Tactile information also allows extracting geometric information from contacts which is a task-independent feature. By learning to map tactile observations to contact shapes, we show robots can reconstruct accurate 3D models of objects, which can later be used for pose estimation. We build on the idea of using geometric information from contacts by developing tools that accurately render contact geometry in simulation. This enables us to develop a probabilistic approach to pose estimation for novel objects based on matching real visuo-tactile observations to a set of simulated ones. As a result, our method does not rely on real data and yields accurate pose distributions. Finally, we demonstrate how this approach to perception enables precise manipulations. In particular, we consider the task of precise pick-and-place of novel objects. Combining perception with task-aware planning, we build a robotic system that identifies in simulation which object grasps will facilitate grasping, planning, and perception; and selects the best one during execution. Our approach adapts to new objects by learning object-dependent models purely in simulation, allowing a robot to manipulate new objects successfully and perform highly accurate placements.
Book Synopsis Visual Control of Robots by : Peter I. Corke
Download or read book Visual Control of Robots written by Peter I. Corke and published by Taylor & Francis Group. This book was released on 1996 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning in Vision-based Robotic Manipulation by : Mengyuan Yan
Download or read book Deep Learning in Vision-based Robotic Manipulation written by Mengyuan Yan and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade, researchers are looking at bringing robots into our daily lives, and automating services such as taxis, delivery, house-works, and even medical procedures. One of the major roadblocks in making this leap is the diversity and uncertainty in the environments that the robots need to work in. Machine perception, i.e. understanding of the environment through visual, audio, and contact signals, is indispensable in such diverse and uncertain environments, and is a hard problem in itself. Further, the environment is changing, due to human activities and other factors, and robots need to react to the changes quickly. Recent developments in deep learning, especially computer vision, has brought us closer to achieving the goal of bringing robots into our daily environments. However, deep learning methods require a large amount of data with annotated labels, and new datasets and annotations need to be collected for each new task. Deep reinforcement learning algorithms have also achieved good performance on a range of locomotion or manipulation tasks, but the amount of interactions required to train most algorithms is so large that it could take days even with parallel simulation engines. Highly data-efficient models and learning algorithms are needed to help robots learn faster and with less human effort. Additionally, when designing a learning-based solution to a robotics task, inference speed needs to be taken into consideration so that the robot can respond to changes quickly. This thesis introduces methods to improve training data efficiency and inference speed for vision-based robotic manipulation. To improve data efficiency of models, we analyze properties and structures of the specific problems, and build structural biases into the models based on the insights obtained. In addition, we demonstrate self-supervised learning of the perception model on real images, enabling robots to collect their own training data without requiring human annotations. To improve robots' response speed, when learning motion policies we design learning algorithms to always explicitly learn the distribution of promising actions, instead of learning an action evaluation function which requires online optimization during runtime. The proposed methods are integrated into end-to-end systems and tested on real robots on two tasks: vision-based robotic grasping, and rope manipulation and knotting.
Book Synopsis Image Processing for Robotic Manipulation by : Andrew Mark Dean
Download or read book Image Processing for Robotic Manipulation written by Andrew Mark Dean and published by . This book was released on 1985 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: As robots are more widely accepted into industrial applications their severe limitations become apparent. Most are unable to recognise the presence of a component let alone say what it is. Robots require the abilities of man, the most useful of which is vision. A robotic vision system must be capable of recognising industrial components and calculating their position and angle of orientation. These computations must be carried out quickly and on a comparatively cheap system to be of any industrial use. This thesis develops such a system. The vision system is based on a Motorola MC68000 16 bit central processing unit, operating a direct- memory -access transfer closed - circuit television camera. The picture data, consisting of an array 256 pixels square at one grey level, is analysed using a decision theoretic recognition approach. This recognition method extracts and compares various features or signatures from the taught and viewed components, these features and their differences provide recognition and orientation information. The final system is capable of recognising a series of complex components, calculating their positions and angular offsets and sending the required data to the robot. Recognition takes less than one second and the value of ....
