Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Robotic Object Pose Estimation With Deep Neural Networks
Download Robotic Object Pose Estimation With Deep Neural Networks full books in PDF, epub, and Kindle. Read online Robotic Object Pose Estimation With Deep Neural Networks ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Robotic Object Pose Estimation with Deep Neural Networks by : Jimmy Wu (M. Eng.)
Download or read book Robotic Object Pose Estimation with Deep Neural Networks written by Jimmy Wu (M. Eng.) and published by . This book was released on 2018 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, we introduce pose interpreter networks for 6-DoF object pose estimation. In contrast to other CNN-based approaches to pose estimation that require expensively-annotated object pose data, our pose interpreter network is trained entirely on synthetic data. We use object masks as an intermediate representation to bridge real and synthetic. We show that when combined with a segmentation model trained on RGB images, our synthetically-trained pose interpreter network is able to generalize to real data. Our end-to-end system for object pose estimation runs in real-time (20 Hz) on live RGB data, without using depth information or ICP refinement.
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 Object Pose Estimation and Tracking with Deep Learning for Robot Manipulation by : Tao Chen
Download or read book Object Pose Estimation and Tracking with Deep Learning for Robot Manipulation written by Tao Chen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Benchmarking Convolutional Neural Networks for Object Segmentation and Pose Estimation by : Tiffany Anh Mai Le
Download or read book Benchmarking Convolutional Neural Networks for Object Segmentation and Pose Estimation written by Tiffany Anh Mai Le and published by . This book was released on 2017 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convolutional neural networks (CNNs), particularly those designed for object segmentation and pose estimation, are now applied to robotics applications involving mobile manipulation. For these robotic applications to be successful, robust and accurate performance from the CNNs is critical. Therefore, in order to develop an understanding of CNN performance, several CNN architectures are benchmarked on a set of metrics for object segmentation and pose estimation. This thesis presents these benchmarking results, which show that metric performance is dependent on the complexity of network architectures. The reasons behind poor pose estimation and object segmentation, which include object symmetry and resolution loss due to downsampling followed by upsampling in the networks, respectively, are also identified in this thesis. These findings can be used to guide and improve the development of CNNs for object segmentation and pose estimation in the future.
Book Synopsis Implicit Object Pose Estimation on RGB Images Using Deep Learning Methods by : Timon Höfer
Download or read book Implicit Object Pose Estimation on RGB Images Using Deep Learning Methods written by Timon Höfer and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rise of robotic and camera systems and the success of deep learning in computer vision, there is growing interest in precisely determining object positions and orientations. This is crucial for tasks like automated bin picking, where a camera sensor analyzes images or point clouds to guide a robotic arm in grasping objects. Pose recognition has broader applications, such as predicting a car's trajectory in autonomous driving or adapting objects in virtual reality based on the viewer's perspective. This dissertation focuses on RGB-based pose estimation methods that use depth information only for refinement, which is a challenging problem. Recent advances in deep learning have made it possible to predict object poses in RGB images, despite challenges like object overlap, object symmetries and more. We introduce two implicit deep learning-based pose estimation methods for RGB images, covering the entire process from data generation to pose selection. Furthermore, theoretical findings on Fourier embeddings are shown to improve the performance of the so-called implicit neural representations - which are then successfully utilized for the task of implicit pose estimation.
Book Synopsis Visual Object Tracking with Deep Neural Networks by : Pier Luigi Mazzeo
Download or read book Visual Object Tracking with Deep Neural Networks written by Pier Luigi Mazzeo and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.
Book Synopsis Deep Learning for Object Detection in Robotic Grasping Contexts by : Jean-Philippe Mercier
Download or read book Deep Learning for Object Detection in Robotic Grasping Contexts written by Jean-Philippe Mercier and published by . This book was released on 2021 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, deep convolutional neural networks became a standard for computer vision applications. As opposed to classical methods which are based on rules and hand-designed features, neural networks are optimized and learned directly from a set of labeled training data specific for a given task. In practice, both obtaining sufficient labeled training data and interpreting network outputs can be problematic. Additionnally, a neural network has to be retrained for new tasks or new sets of objects. Overall, while they perform really well, deployment of deep neural network approaches can be challenging. In this thesis, we propose strategies aiming at solving or getting around these limitations for object detection. First, we propose a cascade approach in which a neural network is used as a prefilter to a template matching approach, allowing an increased performance while keeping the interpretability of the matching method. Secondly, we propose another cascade approach in which a weakly-supervised network generates object-specific heatmaps that can be used to infer their position in an image. This approach simplifies the training process and decreases the number of required training images to get state-of-the-art performances. Finally, we propose a neural network architecture and a training procedure allowing detection of objects that were not seen during training, thus removing the need to retrain networks for new objects.
Book Synopsis Designs and Prototypes of Mobile Robots by : Marco Ceccarelli
Download or read book Designs and Prototypes of Mobile Robots written by Marco Ceccarelli and published by Momentum Press. This book was released on 2015-06-09 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: For several decades now, mobile robots have been integral to the development of new robotic systems for new applications, even in nontechnical areas. Mobile robots have already been developed for such uses as industrial automation, medical care, space exploration, demining operations, surveillance, entertainment, museum guides and many other industrial and non-industrial applications. In some cases these products are readily available on the market. A considerable amount of literature is also available; not all of which pertains to technical issues, as listed in the chapters of this book and its companion. Readers will enjoy this book and its companion and will utilize the knowledge gained with satisfaction and will be assisted by its content in their interdisciplinary work for engineering developments of mobile robots, in both old and new applications. This book and its companion can be used as a graduate level course book or a guide book for the practicing engineer who is working on a specific problem which is described in one of the chapters. The companion volume for this book, Mobile Robots for Dynamic Environments, is also available from Momentum Press.
Book Synopsis Provable and Control-theoretic Methods for Deep Object Pose Estimation by : Trevor Avant
Download or read book Provable and Control-theoretic Methods for Deep Object Pose Estimation written by Trevor Avant and published by . This book was released on 2021 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we consider the task of object pose estimation using deep neural networks. We draw our motivation from the fact that neural networks have shown to be successful at the task of pose estimation, but are poorly theoretically understood and lack meaningful performance guarantees. As a result, our aim in this dissertation is to analyze pose estimation neural networks by developing provable performance guarantees, as well as connecting pose estimation to control theory. We take four different approaches in our analysis. First, we consider object pose estimation from the standpoint of observability in control theory, using the observability Gramian as our main tool for analysis. Next, we explore the idea of estimating the pose of a dynamic object by applying an unscented filter to pose estimates from a neural network. Next, we derive analytical bounds on the local Lipschitz constants of neural networks with ReLU activations. Finally, we consider the task of developing sensitivity bounds for pose estimation neural networks, and construct a pose estimation network with provable bounds for both the rotation and position estimates.
Book Synopsis Proceedings of 3rd International Conference on Artificial Intelligence, Robotics, and Communication by : Sanjay Yadav
Download or read book Proceedings of 3rd International Conference on Artificial Intelligence, Robotics, and Communication written by Sanjay Yadav and published by Springer Nature. This book was released on with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Frontiers of Computer Vision by : Kazuhiko Sumi
Download or read book Frontiers of Computer Vision written by Kazuhiko Sumi and published by Springer Nature. This book was released on 2022-05-16 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the 28th International Workshop on Frontiers of Computer Vision, IW-FCV 2022, held in Hiroshima, Japan, in February 2022. Due to the COVID-19 pandemic the conference was held online. The 24 full papers presented in this volume were thoroughly reviewed and selected from 63 submissions. The papers are organized according to the following topics: camera, 3D, and imaging; learning algorithm; object detection/segmentation; recognition/generation.
Download or read book Robotics Research written by Tamim Asfour and published by Springer Nature. This book was released on 2022-02-17 with total page 1023 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the papers that were presented at the 17th International Symposium of Robotics Research (ISRR). The ISRR promotes the development and dissemination of groundbreaking research and technological innovation in robotics useful to society by providing a lively, intimate, forward-looking forum for discussion and debate about the current status and future trends of robotics with great emphasis on its potential role to benefit humankind. The symposium contributions contained in this book report on a variety of new robotics research results covering a broad spectrum organized into the categories: design, control; grasping and manipulation, planning, robot vision, and robot learning.
Book Synopsis TRUST IN ROBOTS by : Sabine T. Koeszegi
Download or read book TRUST IN ROBOTS written by Sabine T. Koeszegi and published by TU Wien Academic Press. This book was released on 2022-12-15 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robots are increasingly becoming prevalent in our daily lives within our living or working spaces. We hope that robots will take up tedious, mundane or dirty chores and make our lives more comfortable, easy and enjoyable by providing companionship and care. However, robots may pose a threat to human privacy, safety and autonomy; therefore, it is necessary to have constant control over the developing technology to ensure the benevolent intentions and safety of autonomous systems. Building trust in (autonomous) robotic systems is thus necessary. The title of this book highlights this challenge: “Trust in robots—Trusting robots”. Herein, various notions and research areas associated with robots are unified. The theme “Trust in robots” addresses the development of technology that is trustworthy for users; “Trusting robots” focuses on building a trusting relationship with robots, furthering previous research. These themes and topics are at the core of the PhD program “Trust Robots” at TU Wien, Austria.
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 Intelligent Robotics and Applications by : Huayong Yang
Download or read book Intelligent Robotics and Applications written by Huayong Yang and published by Springer Nature. This book was released on 2023-10-20 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023. The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows: Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application. Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot. Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots. Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots. Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots. Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics. Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction. Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms. Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.
Book Synopsis Computer Vision – ECCV 2022 by : Shai Avidan
Download or read book Computer Vision – ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-11-10 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Book Synopsis Computer Vision – ECCV 2022 Workshops by : Leonid Karlinsky
Download or read book Computer Vision – ECCV 2022 Workshops written by Leonid Karlinsky and published by Springer Nature. This book was released on 2023-02-18 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge.
