Deep Self Modeling For Robotic Systems
DOWNLOAD
Download Deep Self Modeling For Robotic Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Self Modeling For Robotic Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Deep Self Modeling For Robotic Systems
DOWNLOAD
Author : Robert Kwiatkowski
language : en
Publisher:
Release Date : 2022
Deep Self Modeling For Robotic Systems written by Robert Kwiatkowski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
As self-awareness is important to human higher level cognition so too is the ability to self-model important to performing complex behaviors. The power of these self-models is one that I demonstrate grows with the complexity of problems being solved, and thus provides the framework for higher level cognition. I demonstrate that self-models can be used to effectively control and improve on existing control algorithms to allow agents to perform complex tasks. I further investigate new ways in which these self-models can be learned and applied to increase their efficacy and improve the ability of these models to generalize across tasks and bodies. Finally, I demonstrate the overall power of these self-models to allow for complex tasks to be completed with little data across a variety of bodies and using a number of algorithms.
Model Based Self Supervision For Fine Grained Image Understanding
DOWNLOAD
Author : Tanner Schmidt
language : en
Publisher:
Release Date : 2019
Model Based Self Supervision For Fine Grained Image Understanding written by Tanner Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
In order to enable robots that perform tasks capably, efficiently, and safely in dynamic environments, we'll need vision systems that are adaptable and can reliably provide detailed and accurate information about the world around the robot. Generative model-based methods are well suited to these demands, as generative models are portable (they are equally valid in many different environments), modular (they can be dynamically combined with other models), and interpretable (via likelihood functions and explicitly parameterized state spaces). For robotics applications, these properties give model-based vision an advantage over the currently dominant deep learning paradigm in computer vision. However, generative models are limited by the curse of dimensionality and data association ambiguity, and are thus plagued by a lack of robustness which is an impediment to successful deployment in robotic systems. This dissertation advances the argument that the strengths and weaknesses of generative model-based vision and discriminative learning-based vision are largely complementary, and can therefore be used to mutual advantage. Specifically, we'll show that generative models can be employed to automate the process of labeling data for supervised training of deep neural networks, demonstrating the benefit to deep learning offered by model-based vision. Then, we'll show that deep neural networks trained to recognize parts of generative models can be used to help resolve ambiguous data association and thus enhance the robustness of state estimation, demonstrating the benefits deep learning can bring back to model-based vision. Overall, we lay out a vision for future development of highly capable robot perception systems in which machine learning expands the envelope of situations in which generative model-based techniques are reliably applicable, and the generative model-based techniques return the favor by providing labels for further training of the network.
Multiagent Robotic Systems
DOWNLOAD
Author : Jiming Liu
language : en
Publisher: CRC Press
Release Date : 2018-10-08
Multiagent Robotic Systems written by Jiming Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Technology & Engineering categories.
Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution. After reading this book you will be able to fully appreciate the strengths and usefulness of various approaches in the development and application of multiagent robotic systems. It covers: Why and how to develop and experimentally test the computational mechanisms for learning and evolving sensory-motor control behaviors in autonomous robots How to design and develop evolutionary algorithm-based group behavioral learning mechanisms for the optimal emergence of group behaviors How to enable group robots to converge to a finite number of desirable task states through group learning What are the effects of the local learning mechanisms on the emergent global behaviors How to use decentralized, self-organizing autonomous robots to perform cooperative tasks in an unknown environment Earlier works have focused primarily on how to navigate in a spatially unknown environment, given certain predefined motion behaviors. What is missing, however, is an in-depth look at the important issues on how to effectively obtain such behaviors in group robots and how to enable behavioral learning and adaptation at the group level. Multiagent Robotic Systems examines the key methodological issues and gives you an understanding of the underlying computational models and techniques for multiagent systems.
Ai Based Robot Safe Learning And Control
DOWNLOAD
Author : Xuefeng Zhou
language : en
Publisher: Springer Nature
Release Date : 2020-06-02
Ai Based Robot Safe Learning And Control written by Xuefeng Zhou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Technology & Engineering categories.
This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.
Deep Learning For Robot Perception And Cognition
DOWNLOAD
Author : Alexandros Iosifidis
language : en
Publisher: Academic Press
Release Date : 2022-02-04
Deep Learning For Robot Perception And Cognition written by Alexandros Iosifidis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Computers categories.
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
Distributed Autonomous Robotic Systems 8
DOWNLOAD
Author : Hajime Asama
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-05-15
Distributed Autonomous Robotic Systems 8 written by Hajime Asama 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 2009-05-15 with Technology & Engineering categories.
The International Symposia on Distributed Autonomous Robotic Systems (DARS) started at Riken, Japan in 1992. Since then, the DARS symposia have been held every two years: in 1994 and 1996 in Japan (Riken, Wako), in 1998 in Germany (Karlsruhe), in 2000 in the USA (Knoxville, TN), in 2002 in Japan (Fukuoka), in 2004 in France (Toulouse), and in 2006 in the USA (Minneapolis, MN). The 9th DARS symposium, which was held during November 17–19 in T- kuba, Japan, hosted 84 participants from 13 countries. The 48 papers presented there were selected through rigorous peer review with a 50% acceptance ratio. Along with three invited talks, they addressed the spreading research fields of DARS, which are classifiable along two streams: theoretical and standard studies of DARS, and interdisciplinary studies using DARS concepts. The former stream includes multi-robot cooperation (task assignment methodology among multiple robots, multi-robot localization, etc.), swarm intelligence, and modular robots. The latter includes distributed sensing, mobiligence, ambient intelligence, and mul- agent systems interaction with human beings. This book not only offers readers the latest research results related to DARS from theoretical studies to application-oriented ones; it also describes the present trends of this field. With the diversity and depth revealed herein, we expect that DARS technologies will flourish soon.
Multi Body Dynamic Modeling Of Multi Legged Robots
DOWNLOAD
Author : Abhijit Mahapatra
language : en
Publisher: Springer Nature
Release Date : 2020-02-27
Multi Body Dynamic Modeling Of Multi Legged Robots written by Abhijit Mahapatra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-27 with Computers categories.
This book describes the development of an integrated approach for generating the path and gait of realistic hexapod robotic systems. It discusses in detail locomation with straight-ahead, crab and turning motion capabilities in varying terrains, like sloping surfaces, staircases, and various user-defined rough terrains. It also presents computer simulations and validation using Virtual Prototyping (VP) tools and real-world experiments. The book also explores improving solutions by applying the developed nonlinear, constrained inverse dynamics model of the system formulated as a coupled dynamical problem based on the Newton–Euler (NE) approach and taking into account realistic environmental conditions. The approach is developed on the basis of rigid multi-body modelling and the concept that there is no change in the configuration of the system in the short time span of collisions.
A Journey From Robot To Digital Human
DOWNLOAD
Author : Edward Y L Gu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-07-24
A Journey From Robot To Digital Human written by Edward Y L Gu 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 2013-07-24 with Technology & Engineering categories.
This book provides readers with a solid set of diversified and essential tools for the theoretical modeling and control of complex robotic systems, as well as for digital human modeling and realistic motion generation. Following a comprehensive introduction to the fundamentals of robotic kinematics, dynamics and control systems design, the author extends robotic modeling procedures and motion algorithms to a much higher-dimensional, larger scale and more sophisticated research area, namely digital human modeling. Most of the methods are illustrated by MATLABTM codes and sample graphical visualizations, offering a unique closed loop between conceptual understanding and visualization. Readers are guided through practicing and creating 3D graphics for robot arms as well as digital human models in MATLABTM, and through driving them for real-time animation. This work is intended to serve as a robotics textbook with an extension to digital human modeling for senior undergraduate and graduate engineering students. At the same time, it represents a comprehensive reference guide for all researchers, scientists and professionals eager to learn the fundamentals of robotic systems as well as the basic methods of digital human modeling and motion generation.
Modeling Simulation And Control Of Ai Robotics And Autonomous Systems
DOWNLOAD
Author : Choudhury, Tanupriya
language : en
Publisher: IGI Global
Release Date : 2024-05-23
Modeling Simulation And Control Of Ai Robotics And Autonomous Systems written by Choudhury, Tanupriya and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-23 with Computers categories.
The chasm between the physical capabilities of Intelligent Robotics and Autonomous Systems (IRAS) and their cognitive potential presents a formidable challenge. While these machines exhibit astonishing strength, precision, and speed, their intelligence and adaptability lag far behind. This inherent limitation obstructs the realization of autonomous systems that could reshape industries, from self-driving vehicles to industrial automation. The solution to this dilemma is unveiled within the pages of Modeling, Simulation, and Control of AI Robotics and Autonomous Systems. Find within the pages of this book answers for the cognitive deficit within IRAS. While these systems boast remarkable physical capabilities, their potential for intelligent decision-making and adaptation remains stunted, thereby bringing innovation to a halt. Solving this issue would mean the re-acceleration of multiple industries that could utilize automation to prevent humans from needing to do work that is dangerous, and could revolutionize transportation, and more.
Simulation Modeling And Programming For Autonomous Robots
DOWNLOAD
Author : Itsuki Noda
language : en
Publisher: Springer
Release Date : 2012-10-20
Simulation Modeling And Programming For Autonomous Robots written by Itsuki Noda and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-20 with Computers categories.
This book constitutes the refereed proceedings of the Third International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2012, held in Tsukuba, Japan, in November 2012. The 33 revised full papers and presented together with 3 invited talks were carefully reviewed and selected from 46 submissions. Ten papers describe design of complex behaviors of autonomous robots, 9 address software layers, 8 papers refer to related modeling and learning. The papers are organized in topical sections on mobile robots, software modeling and architecture and humanoid and biped robots.