Download or read book Planning Algorithms written by Steven M. LaValle and published by Cambridge University Press. This book was released on 2006-05-29 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.

Download or read book Assistive Robotics Proceedings Of The 18th International Conference On Climbing And Walking Robots And The Support Technologies For Mobile Machines Clawar 2015 written by Mohammad Osman Tokhi and published by World Scientific. This book was released on 2015-08-13 with total page 783 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art scientific and engineering research findings and developments in the area of mobile robotics and associated support technologies around the theme of assistive robotics. The book contains peer reviewed articles presented at the CLAWAR 2015 conference. The book contains a comprehensive collection of papers on legged locomotion with numbers of legs from two upward to multi-legs, which includes robots cable of climbing walls, poles, or more complex structures such as continuing the distinctive CLAWAR themes. There are also a strong showing of articles covering human assist devices, notably exoskeletal and prosthetic devices, as well as social robots designed to meet the growing challenges of global ageing population.

Download or read book Learning for Adaptive and Reactive Robot Control written by Aude Billard and published by MIT Press. This book was released on 2022-02-08 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning and Optimization Techniques for Automotive Cyber Physical Systems written by Vipin Kumar Kukkala and published by Springer Nature. This book was released on 2023-10-03 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

Download or read book 32nd European Symposium on Computer Aided Process Engineering written by Ludovic Montastruc and published by Elsevier. This book was released on 2022-06-30 with total page 1760 pages. Available in PDF, EPUB and Kindle. Book excerpt: 32nd European Symposium on Computer Aided Process Engineering: ESCAPE-32 contains the papers presented at the 32nd European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Toulouse, France. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students and consultants for chemical industries who work in process development and design. - Presents findings and discussions from the 32nd European Symposium of Computer Aided Process Engineering (ESCAPE) event

Download or read book Proceedings of the 2018 International Symposium on Experimental Robotics written by Jing Xiao and published by Springer Nature. This book was released on 2020-01-22 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to the contributions presented at the 2018 International Symposium on Experimental Robotics (ISER 2018), this book features summaries of the discussions that were held during the event in Buenos Aires, Argentina. These summaries, authored by leading researchers and session organizers, offer important insights on the issues that drove the symposium debates. Readers will find cutting-edge experimental research results from a range of robotics domains, such as medical robotics, unmanned aerial vehicles, mobile robot navigation, mapping and localization, field robotics, robot learning, robotic manipulation, human–robot interaction, and design and prototyping. In this unique collection of the latest experimental robotics work, the common thread is the experimental testing and validation of new ideas and methodologies. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a dedicated forum for experimental robotics research. In recent years, robotics has broadened its scientific scope, deepened its methodologies and expanded its applications. However, the significance of experiments remains at the heart of the discipline. The ISER gatherings are an essential venue where scientists can meet and have in-depth discussions on robotics based on this central tenet.

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Download or read book Computing and Machine Learning written by Jagdish Chand Bansal and published by Springer Nature. This book was released on with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

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 Machine Learning and Optimization Models for Optimization in Cloud written by Punit Gupta and published by CRC Press. This book was released on 2022-02-27 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition. This book discusses the future improvements and possible intelligent optimization models using artificial intelligence, deep learning techniques and other hybrid models to improve the performance of cloud. Various methods to enhance the directivity of cloud services have been presented which would enable cloud to provide better services, performance and quality of service to user. It talks about the next generation intelligent optimization and fault model to improve security and reliability of cloud. Key Features · Comprehensive introduction to cloud architecture and its service models. · Vulnerability and issues in cloud SAAS, PAAS and IAAS · Fundamental issues related to optimizing the performance in Cloud Computing using meta-heuristic, AI and ML models · Detailed study of optimization techniques, and fault management techniques in multi layered cloud. · Methods to improve reliability and fault in cloud using nature inspired algorithms and artificial neural network. · Advanced study of algorithms using artificial intelligence for optimization in cloud · Method for power efficient virtual machine placement using neural network in cloud · Method for task scheduling using metaheuristic algorithms. · A study of machine learning and deep learning inspired resource allocation algorithm for cloud in fault aware environment. This book aims to create a research interest & motivation for graduates degree or post-graduates. It aims to present a study on optimization algorithms in cloud for researchers to provide them with a glimpse of future of cloud computing in the era of artificial intelligence.

Download or read book Robotics written by Nicholas Roy and published by MIT Press. This book was released on 2013-07-05 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotics: Science and Systems VIII spans a wide spectrum of robotics, bringing together contributions from researchers working on the mathematical foundations of robotics, robotics applications, and analysis of robotics systems.

Download or read book Proceedings of the International Conference on Advanced Mechanical Engineering Automation and Sustainable Development 2021 AMAS2021 written by Banh Tien Long and published by Springer Nature. This book was released on 2022-05-03 with total page 982 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected, peer-reviewed proceedings of the International Conference on Advanced Mechanical Engineering, Automation and Sustainable Development 2021 (AMAS2021), held in the city of Ha Long, Vietnam, from November 4 to 7, 2021. AMAS2021 is a special meeting of the International Conference on Material, Machines and Methods for Sustainable Development (MMMS), with a strong focus on automation and fostering an overall approach to assist policy makers, industries, and researchers at various levels to position local technological development toward sustainable development. The contributions published in this book stem from a wide spectrum of research, ranging from micro- and nanomaterial design and processing, to special applications in mechanical technology, environmental protection, green development, and climate change mitigation. A large group of contributions selected for these proceedings also focus on modeling and manufacturing of ecomaterials.

Download or read book Advanced technologies for planning and operation of prosumer energy systems written by Bin Zhou and published by Frontiers Media SA. This book was released on 2023-04-28 with total page 1092 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book From batch size 1 to serial production Adaptive robots for scalable and flexible production systems written by Mohamad Bdiwi and published by Frontiers Media SA. This book was released on 2023-05-24 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mastering Robot dynamics written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on an Enlightening Journey to "Mastering Robot Dynamics" In a world driven by automation and robotics, mastering the intricacies of robot dynamics is pivotal for creating advanced robotic systems that move with precision and intelligence. "Mastering Robot Dynamics" is your ultimate guide to navigating the complex world of robot motion, control, and manipulation. Whether you're an engineer, researcher, robotics enthusiast, or student, this book equips you with the knowledge and skills needed to excel in designing and controlling sophisticated robotic mechanisms. About the Book: "Mastering Robot Dynamics" takes you on a transformative journey through the intricacies of robot motion and control, from foundational concepts to advanced techniques. From kinematics and dynamics to trajectory planning and real-time control, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the principles and practical applications in real-world robotic scenarios. Key Features: · Foundational Understanding: Build a solid foundation by comprehending the core principles of robot dynamics, including kinematics, inertia, and motion equations. · Robot Kinematics: Explore forward and inverse kinematics, understanding how robots move and calculating joint configurations. · Robot Dynamics: Dive into the study of forces, torques, and motion equations, learning how robots interact with their environments. · Trajectory Planning: Master the art of planning robot paths and trajectories, considering constraints and optimizing motion sequences. · Sensors and Perception: Gain insights into sensor integration, perception systems, and how robots interact with the world through feedback. · Motion Control: Learn about different types of control strategies, from PID control to advanced techniques like model predictive control. · Collision Avoidance: Understand methods for detecting and avoiding collisions, ensuring safety and reliability in robot operations. · Robot Manipulation: Explore techniques for manipulating objects, including grasp planning, manipulation tasks, and robotic arms. · Challenges and Trends: Discover challenges in robot dynamics, from sensor noise to complex control algorithms, and explore emerging trends shaping the future of robotics. Who This Book Is For: "Mastering Robot Dynamics" is designed for engineers, researchers, robotics enthusiasts, students, and anyone passionate about robotics. Whether you're aiming to enhance your skills or embark on a journey toward becoming a robotics expert, this book provides the insights and tools to navigate the complexities of designing and controlling robotic systems. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast written by Federico Divina and published by MDPI. This book was released on 2021-08-30 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting.