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Ist das voll automatisierte, autonom fahrende Auto zum Greifen nah? Testfahrzeuge und Zulassungen in den USA erwecken diesen Eindruck, werfen aber gleichzeitig viele neue Fragestellungen auf. Wie werden autonome Fahrzeuge in das aktuelle Verkehrssystem integriert? Wie erfolgt ihre rechtliche Einbettung? Welche Risiken bestehen und wie wird mit diesen umgegangen? Und welche Akzeptanz seitens der Gesellschaft sowie des Marktes kann hinsichtlich dieser Entwicklungen überhaupt erwartet werden?Das vorliegende Buch gibt Antworten auf ein breites Spektrum dieser und weiterer Fragen. Expertinnen und Experten aus Deutschland und den USA beschreiben aus ingenieur- und gesellschaftswissenschaftlicher Sicht zentrale Themen im Zusammenhang mit der Automatisierung von Fahrzeugen im öffentlichen Straßenverkehr. Sie zeigen auf, welche „Entscheidungen“ einem autonomen Fahrzeug abverlangt werden beziehungsweise welche „Ethik“ programmiert werden muss. Die Autorinnen und Autoren diskutieren Erwartungen und Bedenken, die die individuelle wie auch die gesellschaftliche Akzeptanz des autonomen Fahrens kennzeichnen. Ein durch autonome Fahrzeuge erhöhtes Sicherheitspotenzial wird den Herausforderungen und Lösungsansätzen, die bei der Absicherung des Sicherheitskonzeptes eine Rolle spielen, gegenübergestellt. Zudem erläutern sie, welche Veränderungsmöglichkeiten und Chancen sich für unsere Mobilität und die Neuorganisation des Verkehrsgeschehens ergeben, nicht zuletzt auch für den Güterverkehr. Das Buch bietet somit eine aktuelle, umfassende und wissenschaftlich fundierte Auseinandersetzung mit dem Thema „Autonomes Fahren“.
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This thesis lays the groundwork for the automatic supervision of the laser incision process, which aims to complement surgeons’ perception of the state of tissues and enhance their control over laser incisions. The research problem is formulated as the estimation of variables that are representative of the state of tissues during laser cutting. Prior research in this area leveraged numerical computation methods that bear a high computational cost and are not straightforward to use in a surgical setting. This book proposes a novel solution to this problem, using models inspired by the ability of experienced surgeons to perform precise and clean laser cutting. It shows that these new models, which were extracted from experimental data using statistical learning techniques, are straightforward to use in a surgical setup, allowing greater precision in laser-based surgical procedures.
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This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.
Robotics and Automation --- Control and Systems Theory --- Artificial Intelligence --- Robotic Engineering --- Safe Control --- Deep Reinforcement Learning --- Recurrent Neural Network --- Force Control --- Obstacle Ovoidance --- Adaptive Control --- Trajectory Tracking --- Open Access --- Robotics --- Automatic control engineering --- Artificial intelligence
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This Open Access proceedings present a good overview of the current research landscape of industrial robots. The objective of MHI Colloquium is a successful networking at academic and management level. Thereby the colloquium is focussing on a high level academic exchange to distribute the obtained research results, determine synergetic effects and trends, connect the actors personally and in conclusion strengthen the research field as well as the MHI community. Additionally there is the possibility to become acquainted with the organizing institute. Primary audience are members of the scientific association for assembly, handling and industrial robots (WG MHI).
Robotics and Automation --- Manufacturing, Machines, Tools, Processes --- Engineering Design --- Simulation and Modeling --- Machinery and Machine Elements --- Control, Robotics, Automation --- Machines, Tools, Processes --- Computer Science --- Open Access --- Assembly Processes & Systems --- Handling & Grasping --- Modelling & Simulation --- Human-robot-collaboration --- Industrial Robotics --- Robotics --- Production engineering --- Technical design --- Computer modelling & simulation --- Engines & power transmission
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This open access book reports on cutting-edge electrical engineering and microelectronics solutions to foster and support digitalization in the semiconductor industry. Based on the outcomes of the European project iDev40, which were presented at the two first conference editions of the European Advances in Digital Transformation Conference (EADCT 2018 and EADTC 2019), the book covers different, multidisciplinary aspects related to digital transformation, including technological and industrial developments, as well as human factors research and applications. Topics include modeling and simulation methods in semiconductor operations, supply chain management issues, employee training methods and workplaces optimization, as well as smart software and hardware solutions for semiconductor manufacturing. By highlighting industrially relevant developments and discussing open issues related to digital transformation, the book offers a timely, practice-oriented guide to graduate students, researchers and professionals interested in the digital transformation of manufacturing domains and work environments.
Cyber-physical systems, IoT --- Engineering Economics, Organization, Logistics, Marketing --- Robotics and Automation --- Cyber-Physical Systems --- Industrial Management --- Industrial Automation --- Open Access --- Semantic Web Technologies --- Simulation-based Decision Making --- Cycle Time Modeling --- Automated Material Handling system --- Material Flow Simulation --- Digitalized Workplaces --- Automated Decision-making --- Cross Factory Decision-making --- Mixed Criticality Systems --- Digital twin --- Rapid Prototyping --- System dynamic simulation --- Return on quality --- iDev40 --- EADTC 2018 --- EADTC 2019 --- Electrical engineering --- Cybernetics & systems theory --- Engineering: general --- Management of specific areas --- Robotics
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This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.
Robotics and Automation --- Bayesian Inference --- Control, Robotics, Mechatronics --- Machine Learning --- Mathematical Modeling and Industrial Mathematics --- Robotic Engineering --- Control, Robotics, Automation --- Collaborative Robot Introspection --- Nonparametric Bayesian Inference --- Anomaly Monitoring and Diagnosis --- Multimodal Perception --- Anomaly Recovery --- Human-robot Collaboration --- Robot Safety and Protection --- Hidden Markov Model --- Robot Autonomous Manipulation --- open access --- Robotics --- Bayesian inference --- Automatic control engineering --- Electronic devices & materials --- Machine learning --- Mathematical modelling --- Maths for engineers
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