Task-space Separation Principle

Task-space Separation Principle

Author: Paolo Tommasino

Publisher: Springer

ISBN: 9789811303531

Category: Technology & Engineering

Page: 105

View: 114

This book addresses two fundamental issues of motor control for both humans and robots: kinematic redundancy and the posture/movement problem. It blends traditional robotic constrained-optimal approaches with neuroscientific and evidence-based principles, proposing a “Task-space Separation Principle,” a novel scheme for planning both posture and movement in redundant manipulators. The proposed framework is first tested in simulation and then compared with experimental motor strategies displayed by humans during redundant pointing tasks. The book also shows how this model builds on and expands traditional formulations such as the Passive Motion Paradigm and the Equilibrium Point Theory. Lastly, breaking with the neuroscientific tradition of planar movements and linear(ized) kinematics, the theoretical formulation and experimental scenarios are set in the nonlinear space of 3D rotations which are essential for wrist motions, a somewhat neglected area despite its importance in daily tasks.

Task-space Separation Principle

Task-space Separation Principle

Author: Paolo Tommasino

Publisher: Springer

ISBN: 9811303525

Category: Technology & Engineering

Page: 105

View: 707

This book addresses two fundamental issues of motor control for both humans and robots: kinematic redundancy and the posture/movement problem. It blends traditional robotic constrained-optimal approaches with neuroscientific and evidence-based principles, proposing a “Task-space Separation Principle,” a novel scheme for planning both posture and movement in redundant manipulators. The proposed framework is first tested in simulation and then compared with experimental motor strategies displayed by humans during redundant pointing tasks. The book also shows how this model builds on and expands traditional formulations such as the Passive Motion Paradigm and the Equilibrium Point Theory. Lastly, breaking with the neuroscientific tradition of planar movements and linear(ized) kinematics, the theoretical formulation and experimental scenarios are set in the nonlinear space of 3D rotations which are essential for wrist motions, a somewhat neglected area despite its importance in daily tasks.

Neural & Bio-inspired Processing and Robot Control

Neural & Bio-inspired Processing and Robot Control

Author: Huanqing Wang

Publisher: Frontiers Media SA

ISBN: 9782889456970

Category:

Page: 135

View: 364

This Research Topic presents bio-inspired and neurological insights for the development of intelligent robotic control algorithms. This aims to bridge the inter-disciplinary gaps between neuroscience and robotics to accelerate the pace of research and development.

Advanced, Contemporary Control

Advanced, Contemporary Control

Author: Andrzej Bartoszewicz

Publisher: Springer Nature

ISBN: 9783030509361

Category: Technology & Engineering

Page: 1568

View: 587

This book presents the proceedings of the 20th Polish Control Conference. A triennial event that was first held in 1958, the conference successfully combines its long tradition with a modern approach to shed light on problems in control engineering, automation, robotics and a wide range of applications in these disciplines. The book presents new theoretical results concerning the steering of dynamical systems, as well as industrial case studies and worked solutions to real-world problems in contemporary engineering. It particularly focuses on the modelling, identification, analysis and design of automation systems; however, it also addresses the evaluation of their performance, efficiency and reliability. Other topics include fault-tolerant control in robotics, automated manufacturing, mechatronics and industrial systems. Moreover, it discusses data processing and transfer issues, covering a variety of methodologies, including model predictive, robust and adaptive techniques, as well as algebraic and geometric methods, and fractional order calculus approaches. The book also examines essential application areas, such as transportation and autonomous intelligent vehicle systems, robotic arms, mobile manipulators, cyber-physical systems, electric drives and both surface and underwater marine vessels. Lastly, it explores biological and medical applications of the control-theory-inspired methods.

Advances in Service and Industrial Robotics

Advances in Service and Industrial Robotics

Author: Nikos A. Aspragathos

Publisher: Springer

ISBN: 9783030002329

Category: Technology & Engineering

Page: 747

View: 478

This volume contains the proceedings of the RAAD 2018 conference, covering major areas of research and development in robotics. It provides an overview on the advances in robotics, more specifically in novel design and applications of robotic systems; dexterous grasping, handling and intelligent manipulation; intelligent cooperating and service robots; advanced robot control; human-robot interfaces; robot vision systems and visual serving techniques; mobile robots; humanoid and walking robots; field and agricultural robotics; bio-inspired and swarm robotic systems; developments towards micro and nano-scale robots; aerial, underwater and spatial robots; robot integration in holonic manufacturing; personal robots for ambient assisted living; medical robots and bionic prostheses; intelligent information technologies for cognitive robots etc. The primary audience of the work are researchers as well as engineers in robotics and mechatronics.

Advanced Human-Robot Collaboration in Manufacturing

Advanced Human-Robot Collaboration in Manufacturing

Author: Lihui Wang

Publisher: Springer Nature

ISBN: 9783030691783

Category: Technology & Engineering

Page: 455

View: 219

This book presents state-of-the-art research, challenges and solutions in the area of human–robot collaboration (HRC) in manufacturing. It enables readers to better understand the dynamic behaviour of manufacturing processes, and gives more insight into on-demand adaptive control techniques for industrial robots. With increasing complexity and dynamism in today’s manufacturing practice, more precise, robust and practical approaches are needed to support real-time shop-floor operations. This book presents a collection of recent developments and innovations in this area, relying on a wide range of research efforts. The book is divided into five parts. The first part presents a broad-based review of the key areas of HRC, establishing a common ground of understanding in key aspects. Subsequent chapters focus on selected areas of HRC subject to intense recent interest. The second part discusses human safety within HRC. The third, fourth and fifth parts provide in-depth views of relevant methodologies and algorithms. Discussing dynamic planning and monitoring, adaptive control and multi-modal decision making, the latter parts facilitate a better understanding of HRC in real situations. The balance between scope and depth, and theory and applications, means this book appeals to a wide readership, including academic researchers, graduate students, practicing engineers, and those within a variety of roles in manufacturing sectors.

Text Mining with Machine Learning

Text Mining with Machine Learning

Author: Jan Žižka

Publisher: CRC Press

ISBN: 9780429890277

Category: Computers

Page: 352

View: 837

This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.

Event-Based Control and Signal Processing

Event-Based Control and Signal Processing

Author: Marek Miskowicz

Publisher: CRC Press

ISBN: 9781482256567

Category: Technology & Engineering

Page: 558

View: 618

Event-based systems are a class of reactive systems deployed in a wide spectrum of engineering disciplines including control, communication, signal processing, and electronic instrumentation. Activities in event-based systems are triggered in response to events usually representing a significant change of the state of controlled or monitored physical variables. Event-based systems adopt a model of calls for resources only if it is necessary, and therefore, they are characterized by efficient utilization of communication bandwidth, computation capability, and energy budget. Currently, the economical use of constrained technical resources is a critical issue in various application domains because many systems become increasingly networked, wireless, and spatially distributed. Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers: Methods of analysis and design of event-based control and signal processing Event-driven control and optimization of hybrid systems Decentralized event-triggered control Periodic event-triggered control Model-based event-triggered control and event-triggered generalized predictive control Event-based intermittent control in man and machine Event-based PID controllers Event-based state estimation Self-triggered and team-triggered control Event-triggered and time-triggered real-time architectures for embedded systems Event-based continuous-time signal acquisition and DSP Statistical event-based signal processing in distributed detection and estimation Asynchronous spike event coding technique with address event representation Event-based processing of non-stationary signals Event-based digital (FIR and IIR) filters Event-based local bandwidth estimation and signal reconstruction Event-Based Control and Signal Processing is the first extensive study on both event-based control and event-based signal processing, presenting scientific contributions at the cutting edge of modern science and engineering.

Modularity in Motor Control: From Muscle Synergies to Cognitive Action Representation

Modularity in Motor Control: From Muscle Synergies to Cognitive Action Representation

Author: Andrea d'Avella

Publisher: Frontiers Media SA

ISBN: 9782889198054

Category: Electronic book

Page: 794

View: 480

Mastering a rich repertoire of motor behaviors, as humans and other animals do, is a surprising and still poorly understood outcome of evolution, development, and learning. Many degrees-of-freedom, non-linear dynamics, and sensory delays provide formidable challenges for controlling even simple actions. Modularity as a functional element, both structural and computational, of a control architecture might be the key organizational principle that the central nervous system employs for achieving versatility and adaptability in motor control. Recent investigations of muscle synergies, motor primitives, compositionality, basic action concepts, and related work in machine learning have contributed to advance, at different levels, our understanding of the modular architecture underlying rich motor behaviors. However, the existence and nature of the modules in the control architecture is far from settled. For instance, regularity and low-dimensionality in the motor output are often taken as an indication of modularity but could they simply be a byproduct of optimization and task constraints? Moreover, what are the relationships between modules at different levels, such as muscle synergies, kinematic invariants, and basic action concepts? One important reason for the new interest in understanding modularity in motor control from different viewpoints is the impressive development in cognitive robotics. In comparison to animals and humans, the motor skills of today’s best robots are limited and inflexible. However, robot technology is maturing to the point at which it can start approximating a reasonable spectrum of isolated perceptual, cognitive, and motor capabilities. These advances allow researchers to explore how these motor, sensory and cognitive functions might be integrated into meaningful architectures and to test their functional limits. Such systems provide a new test bed to explore different concepts of modularity and to address the interaction between motor and cognitive processes experimentally. Thus, the goal of this Research Topic is to review, compare, and debate theoretical and experimental investigations of the modular organization of the motor control system at different levels. By bringing together researchers seeking to understand the building blocks for coordinating many muscles, for planning endpoint and joint trajectories, and for representing motor and behavioral actions in memory we aim at promoting new interactions between often disconnected research areas and approaches and at providing a broad perspective on the idea of modularity in motor control. We welcome original research, methodological, theoretical, review, and perspective contributions from behavioral, system, and computational motor neuroscience research, cognitive psychology, and cognitive robotics.

Inventory-Production Theory

Inventory-Production Theory

Author: C.A. Schneeweiss

Publisher: Springer Science & Business Media

ISBN: 9783642953118

Category: Business & Economics

Page: 118

View: 457

The term inventory-production theory is not well defined. It com prises e. g. such models like cash balance models, production smoothing models and pure inventory models. We shall here mainly be concerned with stochastic dynamic problems and shall give exact definitions in the next section. Most of our work will concentrate on cash balance models. However, production smoothing situations and pure inventory problems will also be investigated. Since we are faced in principle with dynamic stochastic situa tions a dynamic programming approach would be appropriate. This approach, however, due to computational restraints, is limited to only but the simplest models. Therefore, in practice, one ruduces stochastics just in taking forecasts of demand and then treating the problem as a deterministic optimization problem. In addition one often introduces certain safety stocks to safeguard the system from possible forecasting errors. In general, this proce dure is suboptimal. However, there exists one particular situa tion when a separation in a forecasting procedure and a subse quent optimization of the remaining deterministic model is not suboptimal. This is known as the linear-quadratic model, i. e. a model having linear system equations and a quadratic cost crite rion. For this type of model H. A. Simon ~3J and later H. Theil [25J have shown that the above separation property holds. In fact, Simon's and Theil's results are nothing else but what has later and more generally become known to control engineers as Kalman's famous separation principle.