Multi-Modal Scene Understanding for Robotic Grasping
Author: Jeannette Bohg
Publisher:
Published: 2011
Total Pages:
ISBN-13:
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Author: Jeannette Bohg
Publisher:
Published: 2011
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Boris Schauerte
Publisher: Springer
Published: 2016-05-11
Total Pages: 220
ISBN-13: 3319337963
DOWNLOAD EBOOKThis book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.
Author: Alexandros Iosifidis
Publisher: Academic Press
Published: 2022-02-04
Total Pages: 638
ISBN-13: 0323885721
DOWNLOAD EBOOKDeep 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
Author: Beatriz León
Publisher: Springer Science & Business Media
Published: 2013-09-29
Total Pages: 263
ISBN-13: 3319018337
DOWNLOAD EBOOKThe human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand’s functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand’s function for grasping and manipulation of everyday life objects. This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.
Author: Hongzhuo Liang
Publisher:
Published: 2022
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKAuthor: Constantine J. Tsikos
Publisher:
Published: 1988
Total Pages: 14
ISBN-13:
DOWNLOAD EBOOKAuthor: Bin Fang
Publisher: Frontiers Media SA
Published: 2021-06-08
Total Pages: 224
ISBN-13: 2889668444
DOWNLOAD EBOOKAuthor: Caihua Xiong
Publisher: World Scientific
Published: 2007
Total Pages: 229
ISBN-13: 9812771832
DOWNLOAD EBOOKThis book provides a fundamental knowledge of robotic grasping and fixturing (RGF) manipulation. For RGF manipulation to become a science rather than an art, the content of the book is uniquely designed for a thorough understanding of the RGF from the multifingered robot hand grasp, basic fixture design principle, and evaluating and planning of robotic grasping/fixturing, and focuses on the modeling and applications of the RGF. Compared with existing publications, this volume concentrates more on abstract formulation, i.e. mathematical modeling of robotic grasping and fixturing. Thus, it will be a good reference text for academic researchers, manufacturing and industrial engineers and a textbook for engineering graduate students.The book provides readers an overall picture and scientific basis of RGF, the comprehensive information and mathematic models of developing and applying RGF in industry, and presents long term valuable information which is essential and can be used by technical professions as a good reference.
Author: Shuiguang Deng
Publisher: Springer Nature
Published: 2022-03-23
Total Pages: 152
ISBN-13: 3030992039
DOWNLOAD EBOOKThis book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually. The 9 full papers were carefully reviewed and selected from 21 submissions. The papers are organized in two topical tracks: mobile application and deep learning, and mobile application with data analysis.
Author: Mahmoud Hassaballah
Publisher: CRC Press
Published: 2020-03-23
Total Pages: 261
ISBN-13: 1351003801
DOWNLOAD EBOOKDeep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.