Download or read book Reinforcement Learning of Locomotion Based on Central Pattern Generators written by and published by . This book was released on 2014 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Towards Autonomous Robotic Systems written by Charles Fox and published by Springer Nature. This book was released on 2021-10-30 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume LNAI 13054 constitutes the refereed proceedings of the 22th Annual Conference Towards Autonomous Robotic Systems, TAROS 2021, held in Lincoln, UK, in September 2021.*The 45 full papers were carefully reviewed and selected from 66 submissions. Organized in the topical sections "Algorithms" and "Systems", they discuss significant findings and advances in the following areas: artificial intelligence; mechatronics; image processing and computer vision; special purpose and application-based systems; user interfaces and human computer interaction. * The conference was held virtually due to the COVID-19 pandemic.

Download or read book Biped Locomotion written by Miomir Vukobratovic and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here for the first time in one book is a comprehensive and systematic approach to the dynamic modeling and control of biped locomotion robots. A survey is included of various approaches to the control of biped robots, and a new approach to the control of biped systems based on a complete dynamic model is presented in detail. The stability of complete biped system is presented for the first time as a highly nonlinear dynamic system. Also included is new software for the synthesis of a dynamically stable walk for arbitrary biped systems, presented here for the first time. A survey of various realizations of biped systems and numerous numerical examples are given. The reader is given a deep insight into the entire area of biped locomotion. The book covers all relevant approaches to the subject and gives the most complete account to date of dynamic modeling, control and realizations of biped systems.

Download or read book Neural Control of Locomotion written by Robert Herman and published by Springer. This book was released on 2017-05-04 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Spiking Central Pattern Generators Through Reverse Engineering of Locomotion Patterns written by Andrés Espinal and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In robotics, there have been proposed methods for locomotion of nonwheeled robots based on artificial neural networks; those built with plausible neurons are called spiking central pattern generators (SCPGs). In this chapter, we present a generalization of reported deterministic and stochastic reverse engineering methods for automatically designing SCPG for legged robots locomotion systems; such methods create a spiking neural network capable of endogenously and periodically replicating one or several rhythmic signal sets, when a spiking neuron model and one or more locomotion gaits are given as inputs. Designed SCPGs have been implemented in different robotic controllers for a variety of robotic platforms. Finally, some aspects to improve and/or complement these SCPG-based locomotion systems are pointed out.

Download or read book Neuro motor control and feed forward models of locomotion in humans written by Marco Iosa and published by Frontiers Media SA. This book was released on 2015-07-29 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Locomotion involves many different muscles and the need of controlling several degrees of freedom. Despite the Central Nervous System can finely control the contraction of individual muscles, emerging evidences indicate that strategies for the reduction of the complexity of movement and for compensating the sensorimotor delays may be adopted. Experimental evidences in animal and lately human model led to the concept of a central pattern generator (CPG) which suggests that circuitry within the distal part of CNS, i.e. spinal cord, can generate the basic locomotor patterns, even in the absence of sensory information. Different studies pointed out the role of CPG in the control of locomotion as well as others investigated the neuroplasticity of CPG allowing for gait recovery after spinal cord lesion. Literature was also focused on muscle synergies, i.e. the combination of (locomotor) functional modules, implemented in neuronal networks of the spinal cord, generating specific motor output by imposing a specific timing structure and appropriate weightings to muscle activations. Despite the great interest that this approach generated in the last years in the Scientific Community, large areas of investigations remain available for further improvement (e.g. the influence of afferent feedback and environmental constrains) for both experimental and simulated models. However, also supraspinal structures are involved during locomotion, and it has been shown that they are responsible for initiating and modifying the features of this basic rhythm, for stabilising the upright walking, and for coordinating movements in a dynamic changing environment. Furthermore, specific damages into spinal and supraspinal structures result in specific alterations of human locomotion, as evident in subjects with brain injuries such as stroke, brain trauma, or people with cerebral palsy, in people with death of dopaminergic neurons in the substantia nigra due to Parkinson’s disease, or in subjects with cerebellar dysfunctions, such as patients with ataxia. The role of cerebellum during locomotion has been shown to be related to coordination and adaptation of movements. Cerebellum is the structure of CNS where are conceivably located the internal models, that are neural representations miming meaningful aspects of our body, such as input/output characteristics of sensorimotor system. Internal model control has been shown to be at the basis of motor strategies for compensating delays or lacks in sensorimotor feedbacks, and some aspects of locomotion need predictive internal control, especially for improving gait dynamic stability, for avoiding obstacles or when sensory feedback is altered or lacking. Furthermore, despite internal model concepts are widespread in neuroscience and neurocognitive science, neurorehabilitation paid far too little attention to the potential role of internal model control on gait recovery. Many important scientists have contributed to this Research Topic with original studies, computational studies, and review articles focused on neural circuits and internal models involved in the control of human locomotion, aiming at understanding the role played in control of locomotion of different neural circuits located at brain, cerebellum, and spinal cord levels.

Download or read book Neurobiology of Motor Control written by Scott L. Hooper and published by John Wiley & Sons. This book was released on 2017-09-05 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multi-disciplinary look at the current state of knowledge regarding motor control and movement—from molecular biology to robotics The last two decades have seen a dramatic increase in the number of sophisticated tools and methodologies for exploring motor control and movement. Multi-unit recordings, molecular neurogenetics, computer simulation, and new scientific approaches for studying how muscles and body anatomy transform motor neuron activity into movement have helped revolutionize the field. Neurobiology of Motor Control brings together contributions from an interdisciplinary group of experts to provide a review of the current state of knowledge about the initiation and execution of movement, as well as the latest methods and tools for investigating them. The book ranges from the findings of basic scientists studying model organisms such as mollusks and Drosophila, to biomedical researchers investigating vertebrate motor production to neuroengineers working to develop robotic and smart prostheses technologies. Following foundational chapters on current molecular biological techniques, neuronal ensemble recording, and computer simulation, it explores a broad range of related topics, including the evolution of motor systems, directed targeted movements, plasticity and learning, and robotics. Explores motor control and movement in a wide variety of organisms, from simple invertebrates to human beings Offers concise summaries of motor control systems across a variety of animals and movement types Explores an array of tools and methodologies, including electrophysiological techniques, neurogenic and molecular techniques, large ensemble recordings, and computational methods Considers unresolved questions and how current scientific advances may be used to solve them going forward Written specifically to encourage interdisciplinary understanding and collaboration, and offering the most wide-ranging, timely, and comprehensive look at the science of motor control and movement currently available, Neurobiology of Motor Control is a must-read for all who study movement production and the neurobiological basis of movement—from molecular biologists to roboticists.

Download or read book Basic Concepts of the Control and Learning Mechanism of Locomotion by the Central Pattern Generator written by Jun Nishii and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this chapter, we introduced the basic concepts of the control and learning mechanism to realize a desired locomotion by the CPG. As introduced in section 5.1, the control system of locomotion in living bodies assumes a hierarchical structure in which the CPG synchronizes with a physical system and generates motor signals to motor neurons, and higher centers learn a desired motor signal from the performance of locomotion and control the CPG. The control signal from higher centers can also function as a teacher signal for the CPG to acquire neural parameters in the CPG. The concept that the higher centers acquire a motor command appears to be a natural assumption because higher centers such as the motor cortex sends motor commands in order to respond to sensory stimulus, e.g., avoiding obstacles. Such hierarchical and multiple control system by higher centers and the CPG also contribute to acquire robust control, as shown in the simulation result in section 5.1. The concept of this model with learning rules for coupled oscillators that send signals to each actuator can be applied to a robot with multi-degree of freedom. However, in order to consider the learning system for locomotion, we should consider the learning mechanism not only for the CPG but also for higher centers. For instance, it appears that higher centers play an important role in shaping the motor command that is generated by the CPG, as mentioned in section 5.2. Another important problem is the explosion of the search space of a motor command, e.g., as the number of actuators increases, that is, as the degree of freedom of a robot increases, the search space for the desired motor command becomes vast. Therefore, it is important to consider an efficient learning mechanism for higher centers to find a desired motor command for each actuator from the performance of locomotion. It has been suggested that locomotor patterns of living bodies are well optimized on energy cost; as mentioned in section 5.2; therefore, the minimization of energy cost would be a constraint.

Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Download or read book Encyclopedia of Computational Neuroscience written by Dieter Jaeger and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Model of Central Pattern Generators for Quadruped Locomotion written by Pietro-Luciano Buono and published by . This book was released on 1998 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Dynamic Balance of Bipedal Robot Based on Central Pattern Generators and Deep Reinforcement Learning written by Christos Kouppas and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Interlimb Coordination written by Stephan P. Swinnen and published by Academic Press. This book was released on 2013-10-22 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive edited treatise discusses the neurological, physiological, and cognitive aspects of interlimb coordination. It is unique in promoting a multidisciplinary perspective through introductory chapter contributions from experts in the neurosciences, experimental and developmental psychology, and kinesiology. Beginning with chapters defining the neural basis of interlimb coordination in animals, the book progresses toward an understanding of human locomotor control and coordination and the underlying brain structures and nerves that make such control possible. Section two focuses on the dynamics of interlimb coordination and the physics of movement. The final section presents information on how practice and experience affect coordination, including general skill acquisition, learning to walk, and the process involved in rhythmic tapping.

Download or read book Humanoid Robotics A Reference written by Prahlad Vadakkepat and published by Springer. This book was released on 2017-02-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humanoid Robotics provides a comprehensive compilation of developments in the conceptualization, design and development of humanoid robots and related technologies. Human beings have built the environment they occupy (living spaces, instruments and vehicles) to suit two-legged systems. Building systems, especially in robotics, that are compatible with the well-established, human-based surroundings and which could naturally interact with humans is an ultimate goal for all researches and engineers. Humanoid Robots are systems (i.e. robots) which mimic human behavior. Humanoids provide a platform to study the construction of systems that behave and interact like humans. A broad range of applications ranging from daily housework to complex medical surgery, deep ocean exploration, and other potentially dangerous tasks are possible using humanoids. In addition, the study of humanoid robotics provides a platform to understand the mechanisms and offers a physical visual of how humans interact, think, and react with the surroundings and how such behaviors could be reassembled and reconstructed. Currently, the most challenging issue with bipedal humanoids is to make them balance on two legs, The purportedly simple act of finding the best balance that enables easy walking, jumping and running requires some of the most sophisticated development of robotic systems- those that will ultimately mimic fully the diversity and dexterity of human beings. Other typical human-like interactions such as complex thought and conversations on the other hand, also pose barriers for the development of humanoids because we are yet to understand fully the way in which we humans interact with our environment and consequently to replicate this in humanoids.

Download or read book Adaptive Motion of Animals and Machines written by Hiroshi Kimura and published by Springer Science & Business Media. This book was released on 2006-07-28 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Motivation It is our dream to understand the principles of animals’ remarkable ability for adaptive motion and to transfer such abilities to a robot. Up to now, mechanisms for generation and control of stereotyped motions and adaptive motions in well-known simple environments have been formulated to some extentandsuccessfullyappliedtorobots.However,principlesofadaptationto variousenvironmentshavenotyetbeenclari?ed,andautonomousadaptation remains unsolved as a seriously di?cult problem in robotics. Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from thecentralnervoussystemtothemusculoskeletalsystem.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines(AMAM)forscientistsandengineersconcernedwithadaptation onvariouslevelstobebroughttogethertodiscussprinciplesateachleveland to investigate principles governing total systems. • History AMAM started in Montreal (Canada) in August 2000. It was organized by H. Kimura (Japan), H. Witte (Germany), G. Taga (Japan), and K. Osuka (Japan), who had agreed that having a small symposium on motion control, with people from several ?elds coming together to discuss speci?c issues, was worthwhile. Those four organizing committee members determined the scope of AMAM as follows.

Download or read book Bioinspired Legged Locomotion written by Maziar Ahmad Sharbafi and published by Butterworth-Heinemann. This book was released on 2017-11-21 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinspired Legged Locomotion: Models, Concepts, Control and Applications explores the universe of legged robots, bringing in perspectives from engineering, biology, motion science, and medicine to provide a comprehensive overview of the field. With comprehensive coverage, each chapter brings outlines, and an abstract, introduction, new developments, and a summary. Beginning with bio-inspired locomotion concepts, the book's editors present a thorough review of current literature that is followed by a more detailed view of bouncing, swinging, and balancing, the three fundamental sub functions of locomotion. This part is closed with a presentation of conceptual models for locomotion. Next, the book explores bio-inspired body design, discussing the concepts of motion control, stability, efficiency, and robustness. The morphology of legged robots follows this discussion, including biped and quadruped designs. Finally, a section on high-level control and applications discusses neuromuscular models, closing the book with examples of applications and discussions of performance, efficiency, and robustness. At the end, the editors share their perspective on the future directions of each area, presenting state-of-the-art knowledge on the subject using a structured and consistent approach that will help researchers in both academia and industry formulate a better understanding of bioinspired legged robotic locomotion and quickly apply the concepts in research or products. Presents state-of-the-art control approaches with biological relevance Provides a thorough understanding of the principles of organization of biological locomotion Teaches the organization of complex systems based on low-dimensional motion concepts/control Acts as a guideline reference for future robots/assistive devices with legged architecture Includes a selective bibliography on the most relevant published articles

Download or read book Beyond Recognition written by Le Minh-Ha and published by Linköping University Electronic Press. This book was released on 2024-05-06 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the need to balance the use of facial recognition systems with the need to protect personal privacy in machine learning and biometric identification. As advances in deep learning accelerate their evolution, facial recognition systems enhance security capabilities, but also risk invading personal privacy. Our research identifies and addresses critical vulnerabilities inherent in facial recognition systems, and proposes innovative privacy-enhancing technologies that anonymize facial data while maintaining its utility for legitimate applications. Our investigation centers on the development of methodologies and frameworks that achieve k-anonymity in facial datasets; leverage identity disentanglement to facilitate anonymization; exploit the vulnerabilities of facial recognition systems to underscore their limitations; and implement practical defenses against unauthorized recognition systems. We introduce novel contributions such as AnonFACES, StyleID, IdDecoder, StyleAdv, and DiffPrivate, each designed to protect facial privacy through advanced adversarial machine learning techniques and generative models. These solutions not only demonstrate the feasibility of protecting facial privacy in an increasingly surveilled world, but also highlight the ongoing need for robust countermeasures against the ever-evolving capabilities of facial recognition technology. Continuous innovation in privacy-enhancing technologies is required to safeguard individuals from the pervasive reach of digital surveillance and protect their fundamental right to privacy. By providing open-source, publicly available tools, and frameworks, this thesis contributes to the collective effort to ensure that advancements in facial recognition serve the public good without compromising individual rights. Our multi-disciplinary approach bridges the gap between biometric systems, adversarial machine learning, and generative modeling to pave the way for future research in the domain and support AI innovation where technological advancement and privacy are balanced.