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14 produkter
14 produkter
Inbunden, Engelska, 2020
1 623 kr
Skickas inom 10-15 vardagar
Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics. This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.
E-bok
Engelska, 20202 049 kr
Läs direkt efter köp
Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics.
This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.
Häftad, Engelska, 2021
1 623 kr
Skickas inom 10-15 vardagar
Over the next few decades, millions of people, with varying backgrounds and levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots will need to infer and predict humans’ intentions and internal objectives on the basis of past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics. This book introduces readers to robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures and other motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation, making it a valuable reference guide for graduate students with a basic knowledge of machine learning, and for researchers interested in wearable computing and robotic learning.
Inbunden, Engelska, 2025
2 161 kr
Skickas inom 10-15 vardagar
Recently, substantial progress has been made in the machine perception, particularly computer vision, largely due to the advancements in deep learning techniques. However, robots often operate in unstructured environments, which differ greatly from the well-defined problems typically addressed in computer vision. Consequently, many existing computer vision solutions are not directly applicable to robotics. Additionally, modern intelligent robots have access to multi-modal sensory information, rather than relying on a single modality. Therefore, it is essential to explore the specific challenges of multi-modal robotic intelligence.A key requirement for all intelligent robots is the capability of active perception. Active perception is an effective approach to bridge the gap between robotics and machine perception. Intelligence emerges when the robot actively interacts with the environment, embodying a close coupling of perception and action within a continuous feedback loop. Perception guided action, and each movement generate information that informs subsequent movements. With a variety of available multi-modal sensory information, it is crucial for robots to leverage active perception techniques to achieve multi-modal robotic intelligence.This book introduces multi-modal robotic intelligence from the perspective of active perception. Extensive robotic multi-modal active perception problems are formulated and corresponding case studies are described. Specifically, this book is organized in three parts. Part I covers core concepts and approaches for multi-modal robotic intelligence. In Part II, active perception for robotic intelligence is described, which presents several typical active perception tasks. Part III further describes the multi-modal active perception for robotic intelligence. The book is primarily intended for researchers and graduates with a foundational knowledge of machine learning, spanning in a wide range of disciplines, particularly those involved in robotic intelligence and sensor fusion.
E-bok
Engelska, 20252 840 kr
Läs direkt efter köp
Recently, substantial progress has been made in the machine perception, particularly computer vision, largely due to the advancements in deep learning techniques. However, robots often operate in unstructured environments, which differ greatly from the well-defined problems typically addressed in computer vision. Consequently, many existing computer vision solutions are not directly applicable to robotics. Additionally, modern intelligent robots have access to multi-modal sensory information, rather than relying on a single modality. Therefore, it is essential to explore the specific challenges of multi-modal robotic intelligence.A key requirement for all intelligent robots is the capability of active perception. Active perception is an effective approach to bridge the gap between robotics and machine perception. Intelligence emerges when the robot actively interacts with the environment, embodying a close coupling of perception and action within a continuous feedback loop. Perception guided action, and each movement generate information that informs subsequent movements. With a variety of available multi-modal sensory information, it is crucial for robots to leverage active perception techniques to achieve multi-modal robotic intelligence.This book introduces multi-modal robotic intelligence from the perspective of active perception. Extensive robotic multi-modal active perception problems are formulated and corresponding case studies are described. Specifically, this book is organized in three parts. Part I covers core concepts and approaches for multi-modal robotic intelligence. In Part II, active perception for robotic intelligence is described, which presents several typical active perception tasks. Part III further describes the multi-modal active perception for robotic intelligence. The book is primarily intended for researchers and graduates with a foundational knowledge of machine learning, spanning in a wide range of disciplines, particularly those involved in robotic intelligence and sensor fusion.
Del 1501 - Lecture Notes in Electrical Engineering
Proceedings of 2025 Chinese Intelligent Automation Conference
Volume I
Inbunden, Engelska, 2025
3 238 kr
Skickas inom 10-15 vardagar
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
E-bok
Engelska, 20253 865 kr
Läs direkt efter köp
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Del 1503 - Lecture Notes in Electrical Engineering
Proceedings of 2025 Chinese Intelligent Automation Conference
Volume III
Inbunden, Engelska, 2026
3 238 kr
Skickas inom 10-15 vardagar
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
E-bok
Engelska, 20263 948 kr
Läs direkt efter köp
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Del 1502 - Lecture Notes in Electrical Engineering
Proceedings of 2025 Chinese Intelligent Automation Conference
Volume II
Inbunden, Engelska, 2026
3 238 kr
Skickas inom 10-15 vardagar
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
E-bok
Engelska, 20263 948 kr
Läs direkt efter köp
This book includes original, peer-reviewed research papers from the 2025 Chinese Intelligent Automation Conference (CIAC2025), held in Hefei, China on July 4-6, 2025. The topics covered include but are not limited to: Intelligent System, Robotics, Control, Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Inbunden, Engelska, 2025
1 946 kr
Skickas inom 10-15 vardagar
In recent years, embodied multi-agent systems, including multi-robots, have emerged as essential solution for demanding tasks such as search and rescue, environmental monitoring, and space exploration. Effective collaboration among these agents is crucial but presents significant challenges due to differences in morphology and capabilities, especially in heterogenous systems. While existing books address collaboration control, perception, and learning, there is a gap in focusing on active perception and interactive learning for embodied multi-agent systems.This book aims to bridge this gap by establishing a unified framework for perception and learning in embodied multi-agent systems. It presents and discusses the perception-action-learning loop, offering systematic solutions for various types of agents—homogeneous, heterogeneous, and ad hoc. Beyond the popular reinforcement learning techniques, the book provides insights into using fundamental models to tackle complex collaboration problems.By interchangeably utilizing constrained optimization, reinforcement learning, and fundamental models, this book offers a comprehensive toolkit for solving different types of embodied multi-agent problems. Readers will gain an understanding of the advantages and disadvantages of each method for various tasks. This book will be particularly valuable to graduate students and professional researchers in robotics and machine learning. It provides a robust learning framework for addressing practical challenges in embodied multi-agent systems and demonstrates the promising potential of fundamental models for scenario generation, policy learning, and planning in complex collaboration problems.
E-bok
Engelska, 20252 524 kr
Läs direkt efter köp
In recent years, embodied multi-agent systems, including multi-robots, have emerged as essential solution for demanding tasks such as search and rescue, environmental monitoring, and space exploration. Effective collaboration among these agents is crucial but presents significant challenges due to differences in morphology and capabilities, especially in heterogenous systems. While existing books address collaboration control, perception, and learning, there is a gap in focusing on active perception and interactive learning for embodied multi-agent systems.
This book aims to bridge this gap by establishing a unified framework for perception and learning in embodied multi-agent systems. It presents and discusses the perception-action-learning loop, offering systematic solutions for various types of agents—homogeneous, heterogeneous, and ad hoc. Beyond the popular reinforcement learning techniques, the book provides insights into using fundamental models to tackle complex collaboration problems.
By interchangeably utilizing constrained optimization, reinforcement learning, and fundamental models, this book offers a comprehensive toolkit for solving different types of embodied multi-agent problems. Readers will gain an understanding of the advantages and disadvantages of each method for various tasks. This book will be particularly valuable to graduate students and professional researchers in robotics and machine learning. It provides a robust learning framework for addressing practical challenges in embodied multi-agent systems and demonstrates the promising potential of fundamental models for scenario generation, policy learning, and planning in complex collaboration problems.
- Nyhet
Häftad, Engelska, 2026
1 946 kr
Skickas inom 10-15 vardagar
In recent years, embodied multi-agent systems, including multi-robots, have emerged as essential solution for demanding tasks such as search and rescue, environmental monitoring, and space exploration. Effective collaboration among these agents is crucial but presents significant challenges due to differences in morphology and capabilities, especially in heterogenous systems. While existing books address collaboration control, perception, and learning, there is a gap in focusing on active perception and interactive learning for embodied multi-agent systems.This book aims to bridge this gap by establishing a unified framework for perception and learning in embodied multi-agent systems. It presents and discusses the perception-action-learning loop, offering systematic solutions for various types of agents—homogeneous, heterogeneous, and ad hoc. Beyond the popular reinforcement learning techniques, the book provides insights into using fundamental models to tackle complex collaboration problems.By interchangeably utilizing constrained optimization, reinforcement learning, and fundamental models, this book offers a comprehensive toolkit for solving different types of embodied multi-agent problems. Readers will gain an understanding of the advantages and disadvantages of each method for various tasks. This book will be particularly valuable to graduate students and professional researchers in robotics and machine learning. It provides a robust learning framework for addressing practical challenges in embodied multi-agent systems and demonstrates the promising potential of fundamental models for scenario generation, policy learning, and planning in complex collaboration problems.