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Titlebook: Informatics in Control, Automation and Robotics; 18th International C Oleg Gusikhin,Kurosh Madani,Henk Nijmeijer Conference proceedings 202

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書目名稱Informatics in Control, Automation and Robotics
副標題18th International C
編輯Oleg Gusikhin,Kurosh Madani,Henk Nijmeijer
視頻videohttp://file.papertrans.cn/465/464870/464870.mp4
概述Highlights the latest research on Informatics in Control, Automation, and Robotics.Includes the extended and revised versions of selected papers from the ICINCO 2021.Written by leading experts in the
叢書名稱Lecture Notes in Electrical Engineering
圖書封面Titlebook: Informatics in Control, Automation and Robotics; 18th International C Oleg Gusikhin,Kurosh Madani,Henk Nijmeijer Conference proceedings 202
描述.The book focuses the latest endeavors relating researches and developments conducted in fields of control, robotics, and automation. Through more than ten revised and extended articles, the present book aims to provide the most up-to-date state of the art of the aforementioned fields allowing researcher, Ph.D. students, and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book...The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same book a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book..
出版日期Conference proceedings 2023
關(guān)鍵詞Informatics in Control, Automation and Robotics; Intelligent Control Systems and Optimization; Robotic
版次1
doihttps://doi.org/10.1007/978-3-031-26474-0
isbn_softcover978-3-031-26476-4
isbn_ebook978-3-031-26474-0Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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A Two-Stage Trajectory Prediction Algorithm for?Mobile Robots Combining the?Bayesian and?the?DMOC Frollisions, and alleviate the communication strain in multi-agent scenarios. Given a well predicted trajectory of the observed other agents, the observer can either establish a clear path to its destination or collaborate with the observed agent in a more energy-efficient manner. To address this chal
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Adaptive Neural Network Based Fractional Order Control of?Unmanned Aerial Vehiclecs of UAV is proposed. The concept of fractional order depicts the more realistic behavior of UAVs. For proposed fractional order model, a fractional order sliding mode controller (SMC) is designed such that the desired path can be achieved by the UAV in finite-time. In addition to this an adaptive
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Pose Optimization of?Task-Redundant Robots in?Second-Order Rest-to-Rest Motion with?Cascaded Dynamicrmance and overall feasibility. Due to high nonlinearity of performance criteria especially for parallel robots a sole local optimization may lead to infeasible solutions for large-scale motion. A pointing task consisting of multiple rest-to-rest trajectories with given dense sample times is regarde
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Prediction of?Overdispersed Count Data Using Real-Time Cluster-Based Discretization of?Explanatory Ved, which is constructed on conditionally independent Gaussian clusters captured in real time using recursive algorithms of the Bayesian mixture estimation theory. The resulting model is expected to be used for predicting count data using real time Gaussian observations. The Poisson distribution of
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