Recent Advances In Robot Learning
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Recent Advances In Robot Learning
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Author : Judy A. Franklin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Recent Advances In Robot Learning written by Judy A. Franklin 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.
Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).
Recent Advances In Robot Learning
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Author : Judy A. Franklin
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-06-30
Recent Advances In Robot Learning written by Judy A. Franklin 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 1996-06-30 with Computers categories.
Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).
Recent Advances In Robot Learning From Demonstration
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Author : Harish Ravichandar
language : en
Publisher:
Release Date : 2020
Recent Advances In Robot Learning From Demonstration written by Harish Ravichandar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
In the context of robotics and automation, learning from demonstration (LfD) is the paradigm in which robots acquire new skills by learning to imitate an expert. The choice of LfD over other robot learning methods is compelling when ideal behavior can be neither easily scripted (as is done in traditional robot programming) nor easily defined as an optimization problem, but can be demonstrated. While there have been multiple surveys of this field in the past, there is a need for a new one given the considerable growth in the number of publications in recent years. This review aims to provide an overview of the collection of machine-learning methods used to enable a robot to learn from and imitate a teacher. We focus on recent advancements in the field and present an updated taxonomy and characterization of existing methods. We also discuss mature and emerging application areas for LfD and highlight the significant challenges that remain to be overcome both in theory and in practice.
Deep Learning For Robot Perception And Cognition
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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 Technology & Engineering 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
Recent Advances In Robotic Systems
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Author : Guanghui Wang
language : en
Publisher: BoD – Books on Demand
Release Date : 2016-09-28
Recent Advances In Robotic Systems written by Guanghui Wang and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-28 with Science categories.
This book brings together some recent advances and development in robotics. In 12 chapters, written by experts and researchers in respective fields, the book presents some up-to-date research ideas and findings in a wide range of robotics, including the design, modeling, control, learning, interaction, and navigation of robots. From an application perspective, the book covers UAVs, USVs, mobile robots, humanoid robots, graspers, and underwater robots. The unique text offers practical guidance to graduate students and researchers in research and applications in the field of robotics.
Advances In Robot Control
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Author : Sadao Kawamura
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-17
Advances In Robot Control written by Sadao Kawamura 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 2007-07-17 with Technology & Engineering categories.
Robotics is still a young science, but we can already identify the people who de?ned its primary course of development. Suguru Arimoto is one of them. His early works laid the foundations of what nowadays is called modern robot control, and we believe it is both appropriate and necessary to write a book on recent advances in this ?eld in the context of his scienti?c interests. While presenting recent advances in robot control is the main intention of this book, we also think it is appropriate to highlight Suguru Arimoto’s research career, main scienti?c achievements, and his personality, too. This can be very inspiring and instructive, especially for young researchers. What are the most remarkable features of Suguru Arimoto? On the p- sonal side, his vitality is striking. He is always focused on a research target, and it is always a fun and a pleasure to discuss with him scienti?c pr- lems and to learn from him. His passion to explain things that might not appear obvious is endless. It is very encouraging to younger researchers that, at this stage of his career, he is still a very active, approachable, and in?u- tial researcher, and a person who leads by example. On the scienti?c side, we should stress his research philosophy. He believes that the ?nal result should be simple and have a clear physical (or physiological, in his recent research) interpretation.
Robot Learning
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Author : J. H. Connell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Robot Learning written by J. H. Connell 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 Technology & Engineering categories.
Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action. Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.
Advances In Robotics Research
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Author : Torsten Kröger
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-05-15
Advances In Robotics Research written by Torsten Kröger 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 German Workshop on Robotics is a convention of roboticists from academia and industry working on mathematical and algorithmic foundations of robotics, on the design and analysis of robotic systems as well as on robotic applications. Selected contributions from researchers in German-speaking countries as well as from the international robotics community compose this volume. The papers are organized in ten scientific tracks: Kinematic and Dynamic Modeling, Motion Generation, Sensor Integration, Robot Vision, Robot Programming, Humanoid Robots, Grasping, Medical Robotics, Autonomous Helicopters, and Robot Applications. Due to an extensive review and discussion process, this collection of scientific contributions is of very high caliber and promises to strongly influence future robotic research activities.
Recent Advances In Robotics And Automation
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Author : Gourab Sen Gupta
language : en
Publisher: Springer
Release Date : 2013-05-23
Recent Advances In Robotics And Automation written by Gourab Sen Gupta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-23 with Technology & Engineering categories.
There isn’t a facet of human life that has not been touched and influenced by robots and automation. What makes robots and machines versatile is their computational intelligence. While modern intelligent sensors and powerful hardware capabilities have given a huge fillip to the growth of intelligent machines, the progress in the development of algorithms for smart interaction, collaboration and pro-activeness will result in the next quantum jump. This book deals with the recent advancements in design methodologies, algorithms and implementation techniques to incorporate intelligence in robots and automation systems. Several articles deal with navigation, localization and mapping of mobile robots, a problem that engineers and researchers are grappling with all the time. Fuzzy logic, neural networks and neuro-fuzzy based techniques for real world applications have been detailed in a few articles. This edited volume is targeted to present the latest state-of-the-art computational intelligence techniques in Robotics and Automation. It is a compilation of the extended versions of the very best papers selected from the many that were presented at the 5th International Conference on Automation, Robotics and Applications (ICARA 2011) which was held in Wellington, New Zealand from 6-8 December, 2011. Scientists and engineers who work with robots and automation systems will find this book very useful and stimulating.
Robot Learning Human Skills And Intelligent Control Design
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Author : Chenguang Yang
language : en
Publisher:
Release Date : 2021
Robot Learning Human Skills And Intelligent Control Design written by Chenguang Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Technology & Engineering categories.
In the last decades robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn manipulation skills from humans. To this end, a number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book introduces recent results on the development of advanced LfD-based learning and control approaches to improve the robot dexterous manipulation. First, there's an introduction to the simulation tools and robot platforms used in the authors' research. In order to enable a robot learning of human-like adaptive skills, the book explains how to transfer a human user's arm variable stiffness to the robot, based on the online estimation from the muscle electromyography (EMG). Next, the motion and impedance profiles can be both modelled by dynamical movement primitives such that both of them can be planned and generalized for new tasks. Furthermore, the book introduces how to learn the correlation between signals collected from demonstration, i.e., motion trajectory, stiffness profile estimated from EMG and interaction force, using statistical models such as hidden semi-Markov model and Gaussian Mixture Regression. Several widely used human-robot interaction interfaces (such as motion capture-based teleoperation) are presented, which allow a human user to interact with a robot and transfer movements to it in both simulation and real-word environments. Finally, improved performance of robot manipulation resulted from neural network enhanced control strategies is presented. A large number of examples of simulation and experiments of daily life tasks are included in this book to facilitate better understanding of the readers.