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Human-Robot Interaction Control Using Reinforcemen t Learning
identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical;
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Dynamics And Robust Control Of Robot-environment Interaction
environment, including the human-robot physical interaction. It provides comprehensive theoretical and experimental coverage of interaction control;
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Intelligent Robotics and Applications
service; neural learning enhanced motion planning and control for human robot interaction; medical engineering.;
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Designing Robot Behavior in Human-Robot Interactions
and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency;
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Designing Robot Behavior in Human-Robot Interactions
and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency;
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Robot Learning Human Skills and Intelligent Control Design
efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book;
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Internet-Based Interaction with Mobile Robots
The human interaction and the robot's autonomy are key functions that can spread the use of the robot in human daily life. The remote;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Intelligent Robotics and Applications
fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control;
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Trends in Control and Decision-Making for Human-Robot Collaboration Systems
robots, abstraction of swarm systems to make them suitable for human control, modeling and control of internal force interactions for;
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Developing an 8 DoF Humanoid and Achieving Human Robot Interaction
are fundamental technologies for Human-Computer interaction. Same technology has been adapted for Human- Robot Interaction. For which a;
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Advanced Technologies in Modern Robotic Applications
, new concepts, novel methods and tools into robot control, robot vision, human robot interaction, teleoperation of robot and multiple robots;
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Kinematic Control of Redundant Robot Arms Using Neural Networks
specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations;
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RoboCup 2016
planning and control, robot learning, multi-robot systems, and human-robot interaction.;
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Biologically Inspired Control of Humanoid Robot Arms
benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates;
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Intelligent Robotics and Applications
systems and distributed control; human-machine interaction; rehabilitation robotics; sensors and actuators; and industrial robot and robot;
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Interactive Collaborative Robotics
. Topics addressed are: assistive robots, child-robot interaction, collaborative robotics, educational robotics, human-robot interaction, medical;
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Sociorobot World
outline of sociorobot intelligent control architectures, robot learning and human robot interaction.;
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Robot Control using an Artificial Neural Network
artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These;
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Advances in Physical Agents II
social robots; multiagent systems; human-robot interaction; perception systems; and deep-learning techniques applied to the robotics. Based on;
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Learning Control
Covers iterative learning impedance control in both human-robot interaction and collaborative robots;
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Human-Friendly Robotics 2020
postgraduates which are doing or willing to do research in fields related to human-friendly robotics, including human-robot interaction, robot control;
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