Motion Control of a Robotic Arm of a Humanoid Robot with Perspective Difference PDF Download
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Author: Colin Killby
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Colin Killby
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Adam Spiers
Publisher: Springer
ISBN: 3319301608
Category : Technology & Engineering
Languages : en
Pages : 286
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This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approaches proposed here promote human-like motion with better exploitation of the robot’s physical structure. This also benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models. The operational-space method of robot control forms the basis of many of the techniques investigated in this book. The method includes attractive features such as the decoupling of motion into task and posture components. Various developments are made in each of these elements. Simple cost functions inspired by biomechanical “effort” and “discomfort” generate realistic posture motion. Sliding-mode techniques overcome robustness shortcomings for practical implementation. Arm compliance is achieved via a method of model-free adaptive control that also deals with actuator saturation via anti-windup compensation. A neural-network-centered learning-by-observation scheme generates new task motions, based on motion-capture data recorded from human volunteers. In other parts of the book, motion capture is used to test theories of human movement. All developed controllers are applied to the reaching motion of a humanoid robot arm and are demonstrated to be practically realisable. This book is designed to be of interest to those wishing to achieve dynamics-based human-like robot-arm motion in academic research, advanced study or certain industrial environments. The book provides motivations, extensive reviews, research results and detailed explanations. It is not only suited to practising control engineers, but also applicable for general roboticists who wish to develop control systems expertise in this area.
Author: 許宣弘
Publisher:
ISBN:
Category :
Languages : en
Pages : 79
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Author: Chenguang Yang
Publisher: CRC Press
ISBN: 1000395170
Category : Computers
Languages : en
Pages : 184
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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.
Author: Tareq Ahram
Publisher: Springer
ISBN: 3319606395
Category : Technology & Engineering
Languages : en
Pages : 276
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Book Description
This book focuses on the human aspects of wearable technologies and game design, which are often neglected. It shows how user centered practices can optimize wearable experience, thus improving user acceptance, satisfaction and engagement towards novel wearable gadgets. It describes both research and best practices in the applications of human factors and ergonomics to sensors, wearable technologies and game design innovations, as well as results obtained upon integration of the wearability principles identified by various researchers for aesthetics, affordance, comfort, contextual-awareness, customization, ease of use, ergonomy, intuitiveness, obtrusiveness, information overload, privacy, reliability, responsiveness, satisfaction, subtlety, user friendliness and wearability. The book is based on the AHFE 2017 Conferences on Human Factors and Wearable Technologies and AHFE 2017 Conferences on Human Factors and Game Design, held on July 17-21, 2017, in Los Angeles, California, USA, and addresses professionals, researchers, and students dealing with the human aspects of wearable, smart and/or interactive technologies and game design research.
Author: Tadej Petric
Publisher: Frontiers Media SA
ISBN: 2889632652
Category :
Languages : en
Pages : 129
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Author: Matteo Bianchi
Publisher: Springer
ISBN: 331926706X
Category : Computers
Languages : en
Pages : 284
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This book looks at the common problems both human and robotic hands encounter when controlling the large number of joints, actuators and sensors required to efficiently perform motor tasks such as object exploration, manipulation and grasping. The authors adopt an integrated approach to explore the control of the hand based on sensorimotor synergies that can be applied in both neuroscience and robotics. Hand synergies are based on goal-directed, combined muscle and kinematic activation leading to a reduction of the dimensionality of the motor and sensory space, presenting a highly effective solution for the fast and simplified design of artificial systems. Presented in two parts, the first part, Neuroscience, provides the theoretical and experimental foundations to describe the synergistic organization of the human hand. The second part, Robotics, Models and Sensing Tools, exploits the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one. Human and Robot Hands provides a valuable reference for students, researchers and designers who are interested in the study and design of the artificial hand.
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
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Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Author: Lei Wu
Publisher:
ISBN:
Category : Robotics
Languages : en
Pages : 96
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We have designed and implemented a novel human-robot teleoperation interface based on an intuitive reference frame and hybrid inverse kinematics to perform activities of daily living(ADL) using multiple input devices. Persons with disabilities often rely on caregivers or family members to assist in their daily living activities. Providing robotic assistants with easy and intuitive user interfaces to assist with ADL can improve their quality of life and lift some of the burdens on caregivers and family members. Current human-robot interface solutions, such as joysticks, Kinect based gesture recognition, and touchscreen-based solutions, including smartphones, are still far from being able to operate in an intuitive way when used for complex activities of daily living. In this dissertation, we review the current popular human-robot interfaces and discuss their advantages and disadvantages. When developing our new interface system, we try to maximize as many advantages as possible while minimizing the disadvantages. In this era of smartphones that are packed with sensors, such as accelerometers, gyroscopes, and a precise touch screen, teleoperation control can be interfaced with smartphones to capture the user's intended operation of the robot assistant. We developed three novel human-robot smartphone-based interfaces to operate a robotic arm for assisting persons with disabilities in their ADL tasks. Useful smartphone data, including 3-dimensional orientation and 2-dimensional touchscreen positions, are used as control variables to the robot motion in Cartesian teleoperation. The developed interfaces provide intuitiveness, low cost, and environmental adaptability. Not only the interface devices affect the intuitiveness of the robotic arm teleoperation, but also the inverse kinematics algorithm of the robotic arm is crucial to the whole system intuitiveness as well. The two commonly used reference frames are the Ground and the End-effector reference frames, which do not always provide intuitive control from the perspective of human operators. We conducted preliminary testing in Ground and End-effector reference frames separately to maneuver objects in 3D space. Based on their feedback, we found how users wanted the robot to move and developed a new Intuitive Reference Frame with a novel hybrid inverse kinematics solution(the Hybrid system). This system provides a more natural and easier to use human-robot interface. Two conventional control reference frames(the Ground and the End-effector) are compared with our novel Intuitive control reference frame. An activity of daily living(ADL) task was used to test the performances of the three control reference frames. A 6-D spacemouse, Xbox controller, Omni and a smartphone were used as input devices for the human-robot interfaces to control a Baxter robotic arm and perform the same ADL task using the three different control reference frames. We tested the three control reference frame systems with human subjects and collected qualitative and quantitative data. The results show that overall our Intuitive robotic arm control reference frame with the hybrid inverse kinematics greatly reduced the time and effort needed to manipulate the robotic arm. The results also show that our Hybrid system improved the performances and intuitiveness for all tested input devices.
Author: Curtis M. Conway
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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