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The book discusses the main methods of iterative learning control (ILC) and its interactions, as well as comparator performance that is so crucial to the end user. The book provides integrated coverage of the major approaches to-date in terms of basic systems, theoretic properties, design algorithms, and experimentally measured performance, as well as the links with repetitive control and other related areas

• Introduction. Intelligent Robotic Systems. Off-Line Planning, Programming, and Simulation of Intelligent Robotic Systems: Virtual Robotic Cells. Planning of Robotic Cell Actions. OffLine Planning of Robot Motion. CAP/CAM Systems for Robotic Cell Design. Event-Based Real-Time Control of Intelligent Robotic Systems using Neural Networks and Fuzzy Logic: The Execution Level of Robotic Agent Action. The Coordination Level of a Multiagent Robotic System. The Organization Level of a Robotic System. RealTime Monitoring. ObjectOriented DiscreteEvent Simulator of Intelligent Robotic Cells. Index.
• (source: Nielsen Book Data)

Here is a comprehensive presentation of methodology for the design and synthesis of an intelligent complex robotic system, connecting formal tools from discrete system theory, artificial intelligence, neural network, and fuzzy logic. The necessary methods for solving real time action planning, coordination and control problems are described. A notable chapter presents a new approach to intelligent robotic agent control acting in a realworld environment based on a lifelong learning approach combining cognitive and reactive capabilities. Another key feature is the homogeneous description of all solutions and methods based on system theory formalism.
(source: Nielsen Book Data)

• 1. Fractional-order calculus, numerical techniques, and applications
• 2. Fractional-order linear circuits and systems: Design and hardware implementation
• 3. Fractional-order chaotic systems and their applications
• 4. Bio-impedance Modeling
• 5. Fractional order modeling of different systems
• 6. Fractional order Chaos control and synchronization
• 7. Fractional order image processing and implementations
• 8. Applications based on fractional-order memristive systems
• 9. Solid-state implementations of fractional-order elements
• 10. Fractional-order non-linear circuits and systems: design and hardware implementation
• 11. Fractional-order systems and applications based on neural networks
• 12. Fractional-order controllers, theory, design, and applications
• 13. Platforms for fractional-order system design
• 14. Fractional-order modeling of supercapacitors and batteries.
• (source: Nielsen Book Data)

Fractional-order Modelling of Dynamic Systems with Applications in Optimization, Signal Processing and Control introduces applications from a design perspective, helping readers plan and design their own applications. The book includes the different techniques employed to design fractional-order systems/devices comprehensively and straightforwardly. Furthermore, mathematics is available in the literature on how to solve fractional-order calculus for system applications. This book introduces the mathematics that has been employed explicitly for fractional-order systems. It will prove an excellent material for students and scholars who want to quickly understand the field of fractional-order systems and contribute to its different domains and applications. Fractional-order systems are believed to play an essential role in our day-to-day activities. Therefore, several researchers around the globe endeavor to work in the different domains of fractional-order systems. The efforts include developing the mathematics to solve fractional-order calculus/systems and to achieve the feasible designs for various applications of fractional-order systems.
(source: Nielsen Book Data)

• Blind Source Separation
• Intelligent Sensor Networks
• Intelligent Control and Automation
• Data Fusion, Knowledge Discovery and Data Mining
• Special Session on Smart and Intelligent Home Technology.

Results of the International Conference on Intelligent Computing, ICIC 2006: Lecture Notes in Computer Science (LNCS), Lecture Notes in Artificial Intelligence (LNAI), Lecture Notes in Bioinformatics (LNBI), Lecture Notes in Control and Information Sciences (LNCIS). 142 revised full papers are organized in topical sections: Blind Source Separation; Intelligent Sensor Networks; Intelligent Control and Automation; and Data Fusion, Knowledge Discovery, and Data Mining. Includes a Special Session on Smart and Intelligent Home Technology.
(source: Nielsen Book Data)

• Part I: Soft Computing.- Pseudo-Analysis in Soft Computing.- Aggregation Functions in Fuzzy Systems.- Neural Networks or Fuzzy Systems.- New IEC Research and Frameworks.- Part II: Intelligent Robotics.- How to Generate and Realize Bipedal Gait in Unstructured Environments?.- PDAC-based Brachiating Control of the Multi-Locomotion Robot.- A Simple Method for Generating Smooth Robot Arm Motion.- Fuzzy Inference-based Mentality Expression for Eye Robot in Affinity Pleasure-Arousal Space.- Fuzzy Communication and Motion Control by Fuzzy Signatures in Intelligent Mobile Robots.- Part III: Intelligent Control.- Linear Switching Systems: Attainability and Controllability.- Indirect Adaptive Control Using Hopfield-based Dynamic Neural Network for SISO Nonlinear Systems.- Fuzzy Immune Controller Synthesis for ABR Traffic Control in High-Speed Networks.- Takagi-Sugeno Type Fuzzy Automaton Model.- Control and Dynamics of Fractional Order Systems.- Adaptive Control Using Fixed Point Transformations for Nonlinear Integer and Fractional Order Dynamic Systems.
• (source: Nielsen Book Data)

Soft computing, as a collection of techniques exploiting approximation and tolerance for imprecision and uncertainty in traditionally intractable problems, has become very effective and popular especially because of the synergy derived from its components. The integration of constituent technologies provides complementary methods that allow developing flexible computing tools and solving complex problems. A wide area of natural applications of soft computing techniques consists of the control of dynamic systems, including robots. Loosely speaking, control can be understood as driving a process to attain a desired goal. Intelligent control can be seen as an extension of this concept, to include autonomous human-like interactions of a machine with the environment. Intelligent robots can be characterized by the ability to operate in an uncertain, changing environment with the help of appropriate sensing. They have the power to autonomously plan and execute motion sequences to achieve a goal specified by a human user without detailed instructions. In this volume leading specialists address various theoretical and practical aspects in soft computing, intelligent robotics and control. The problems discussed are taken from fuzzy systems, neural networks, interactive evolutionary computation, intelligent mobile robotics, and intelligent control of linear and nonlinear dynamic systems.

• Research on Parking Space Allocation of Stereo Garage Based on Improved Genetic Algorithm.- Context-Awareness Based Battlefield Situation Information Recommendation.
• (source: Nielsen Book Data)

The proceedings present selected research papers from the CIAC2021, held in Zhanjiang, China on Nov 5-7, 2021. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.
(source: Nielsen Book Data)

• Learning-based Driver Workload Estimation.- Visual Monitoring of Driver Inattention.- Understanding Driving Activity Using Ensemble Methods.- Computer Vision and Machine Learning for Enhancing Pedestrian Safety.- Application of Graphical Models in the Automotive Industry.- Extraction of Maximum Support Rules for the Root Cause Analysis.- Neural networks in automotive applications.- On learning machines for engine control.
• (source: Nielsen Book Data)

This edited volume is the first of its kind and provides a representative sample of contemporary computational intelligence (CI) activities in the area of automotive technology. All chapters contain overviews of the state-of-the-art.

• Introduction.- Stabilization Synthesis of T-S Fuzzy Delayed Systems.- Output Feedback Control of Fuzzy Stochastic Systems.- Output Feedback Control of Fuzzy Switching Systems.- Dissipative Filtering of Fuzzy Switched Systems.- Fault Detection for Switched Stochastic Systems.- Reliable Filtering for T-S Fuzzy Time-Delay Systems.- Reduced-Order Model Approximation of Switched Systems.- Model Reduction of Time-Varying Delay Fuzzy Systems.- Model Approximation of Fuzzy Switched Systems.- Reduced-Order Filter Design of Fuzzy Stochastic Systems.- Dissipative Event-Triggered Fuzzy Control of Truck-Trailer Systems.- Event-Triggered Fuzzy Control of Inverted Pendulum Systems.- Conclusion and Further Work.
• (source: Nielsen Book Data)

This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model-based systems. A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some efficient techniques, such as Lyapunov stability theory, linear matrix inequality, reciprocally convex approach, and cone complementary linearization method, are utilized in the approaches. This book is a comprehensive reference for researchers and practitioners working on intelligent control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts and methodologies with theoretical and practical significance in system analysis and control synthesis.
(source: Nielsen Book Data)

• Chapter 1: Attitude-based multi-expert evaluation of design.-
• Chapter 2: An investigation of hidden shared linkages among perceived causal relationships in cognitive maps.-
• Chapter 3: A new framework for multiple-criteria decision making: The baseline approach.-
• Chapter 4: Fuzzy similarity and entropy (FSAE) feature selection revisited by using intra-class entropy and a normalized scaling factor.-
• Chapter 5: A region-based approach for missing value imputation of cooling technologies for the global thermal power plant fleet using a decision tree classifier.-
• Chapter 6: A neural network based multi-class trading strategy for the S&P 500 index.-
• Chapter 7: Predicting short-term traffic speed and speed drops in the urban area of a medium-sized European city - a traffic control and decision support perspective.-
• Chapter 8: Hedging effectiveness of currency ETFs against WTI crude oil price fluctuations .
• (source: Nielsen Book Data)

This book presents a selection of current research results in the field of intelligent systems and draws attention to their practical applications and issues connected with the areas of decision-making, economics, business and finance. The nature of the contributions is interdisciplinary - combining psychological and behavioural aspects with the theory and practice of decision-support, design of intelligent systems and development of machine learning tools. The authors, among other topics, discuss the multi-expert evaluation with intangible criteria, suggest a redefinition of the standard multiple-criteria decision-making framework, propose novel methods for causal map analysis and new feature selection methods. The topics are selected to stress the potential of the up-to-date intelligent methods to deal with practical problems relevant in these areas and to provide inspiration for advanced students, researchers and practitioners in the respective fields. .
(source: Nielsen Book Data)

• Studies on Driving Behavior
• Hand-Skin Temperature Response to Driving Fatigue: an Exploratory Study
• Toward Driver State Models that Explain Interindividual Variability of Distraction for Adaptive Automation
• Development of a Driving Model that Understands Other Drivers' Characteristics
• Voice User-Interface (VUI) in Automobiles: Exploring Design Opportunities for using VUI through the Observational Study
• Measuring Driver Distraction with the Box Task
• A Summary of Two Experimental Studies
• I Care Who and Where you Are
• Influence of Type, Position and Quantity of Oncoming Vehicles on Perceived Safety during Automated Driving on Rural Roads
• Evaluation of Driver Drowsiness while Using Automated Driving Systems on Driving Simulator, Test Course and Public Roads
• Conflict Situations and Driving Behavior in Road Traffic
• an Analysis using Eyetracking and Stress Measurement on Car Drivers
• Decision-making in Interactions between Two Vehicles at a Highway Junction
• Influencing Driver's Behavior on an Expressway with Intrinsic Motivation
• The Relationship between Drowsiness Level and Takeover Performance in Automated Driving
• Urban and Smart Mobility
• Toolbox for Analysis and Evaluation of Low-Emission Urban Mobility
• Training Pedestrian Safety Skills in Youth with Intellectual Disabilities Using Fully Immersive Virtual Reality
• A Feasibility Study
• A Decision Support System for Terminal Express Delivery Route Planning
• A Tactile Interface to Steer Power Wheelchairs for People Suffering from Neuromuscular Diseases
• A Methodological Approach to Determine the Benefits of External HMI during Interactions between Cyclists and Automated Vehicles: A Bicycle Simulator Study
• Mobility-as-a-Service: Tentative on Users, Use and Effects
• A Passenger Context Model for Adaptive Passenger Information in Public Transport
• An Evaluation Environment for User Studies in the Public Transport Domain
• Design Guidelines for the Simulation of the Usage Context "Station" in VR Environment
• UI Proposal for Shared Autonomous Vehicles: Focusing on Improving User's Trust
• Employees' Vulnerability
• the Challenge When Introducing New Technologies in Local Authorities
• PRONTOMovel
• A Way of Transporting Creativity and Technology
• Multimodal Mobility Packages
• Concepts and Methodological Design Approaches
• A Multi-Device Evaluation Approach of Passenger Information Systems in Smart Public Transport
• Investigating the Influencing Factors of User Experience in Car-sharing Services: an Application of DEMATEL Method
• Assistive Systems for Special Needs in Mobility in the Smart City.

This two-volume set LNCS 12212 and 12213 constitutes the refereed proceedings of the Second International Conference on HCI in Mobility, Transport, and Automotive Systems, MobiTAS 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in Copenhagen, Denmark, in July, 2020.* A total of 1439 full papers and 238 posters have been carefully reviewed and accepted for publication in HCII 2020. The papers cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. MobiTAS 2020 includes a total of 59 papers and they are organized in the following topical sections: Part I, Automated Driving and In-Vehicle Experience Design: UX topics in automated driving, and designing in-vehicle experiences. Part II, Driving Behavior, Urban and Smart Mobility: studies on driving behavior, and urban and smart mobility. *The conference was held virtually due to the COVID-19 pandemic. -- Provided by publisher.

• 1. Introduction
• 2. Nature-inspired algorithms for the optimal tuning of fuzzy controllers
• 3. Adaptive nature-inspired algorithms for the optimal tuning of fuzzy controllers
• 4. Hybrid nature-inspired algorithms for the optimal tuning of fuzzy controllers
• 5. Conclusions.
• (source: Nielsen Book Data)

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems explains fuzzy control in servo systems in a way that doesn't require any solid mathematical prerequisite. Analysis and design methodologies are covered, along with specific applications to servo systems and representative case studies. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation and real-time experimental results. This book is a great resource for a wide variety of readers, including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems.
(source: Nielsen Book Data)

• Chapter 1: An overview of nonlinear identification and control with fuzzy systems
• Chapter 2: An overview of nonlinear identification and control with neural networks
• Chapter 3: Multi-objective evolutionary computing solutions for control and system identification
• Chapter 4: Adaptive local linear modelling and control of nonlinear dynamical systems
• Chapter 5: Nonlinear system identification with local linear neuro-fuzzy models
• Chapter 6: Gaussian process approaches to nonlinear modelling for control
• Chapter 7: Neuro-fuzzy model construction, design and estimation
• Chapter 8: A neural network approach for nearly optimal control of constrained nonlinear systems
• Chapter 9: Reinforcement learning for online control and optimisation
• Chapter 10: Reinforcement learning and multi-agent control within an internet environment
• Chapter 11: Combined computational intelligence and analytical methods in fault diagnosis
• Chapter 12: Application of intelligent control to autonomous search of parking place and parking of vehicles
• Chapter 13: Applications of intelligent control in medicine.
• (source: Nielsen Book Data)

Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.
(source: Nielsen Book Data)

• Stable PID control and systematic tuning of PID gains
• PID control in task space
• PD control with neural compensation
• PID control with neural compensation
• PD control with fuzzy compensation
• PD control with sliding mode compensation
• PID admittance control in task space
• PID admittance control in joint space
• Robot trajectory generation in joint space
• Design of upper limb exoskeletions.

Explains how to use neural PD and PID controls to reduce integration gain, and provides explicit conditions on how to select linear PID gains using proof of semi-global asymptotic stability and local asymptotic stability with a velocity observer. These conditions are applied in both task and joint spaces, with PID controllers compensated by neural networks. This is a great resource on how to combine traditional PD/PID control techniques with intelligent control. Dr. Wen Yu presents several leading-edge methods for designing neural and fuzzy compensators with high-gain velocity observers for PD control using Lyapunov stability. Proportional-integral-derivative (PID) control is widely used in biomedical and industrial robot manipulators. An integrator in a PID controller reduces the bandwidth of the closed-loop system, leads to less-effective transient performance and may even destroy stability. Many robotic manipulators use proportional-derivative (PD) control with gravity and friction compensations, but improved gravity and friction models are needed. The introduction of intelligent control in these systems has dramatically changed the face of biomedical and industrial control engineering.

• Localization and SLAM Online Learning Based Long-Term Feature Existence State Prediction for Visual Topological Localization
• Hongle Xie, Weidong Chen and Jingchuan Wang
• ALOT: Augmented Localization with Obstacle Tracking
• Zhikai Li, Krittin Kawkeeree, Yue Linn Chong, Christina Dao Wen Lee and Marcelo Ang
• RTS-vSLAM: Real-time Visual Semantic Tracking and Mapping under Dynamic Environments
• Yubao Liu and Jun Miura
• Mobile Robot Localization Considering the Attributes of Objects to Prevent the Kidnapped Robot Problem
• Taiki Harada, Ayanori Yorozu and Masaki Takahashi
• Collaborative Mapping of Archaeological Sites using multiple UAVs
• Manthan Patel, Aditya Bandopadhyay and Aamir Ahmad
• 3D Nominal Scene Reconstruction for Object Localization and UAS Navigation
• Xuyang Han and Sutthiphong Srigrarom
• Navigation Topometric Navigation Considering Movable Objects
• Shunsuke Mochizuki, Ayanori Yorozu and Masaki Takahashi
• Harmonious Robot Navigation Strategies for Pedestrians
• Shintaro Nakaoka, Ayanori Yorozu and Masaki Takahashi
• Shared autonomy for telepresence robots based on people-aware navigation
• Gloria Beraldo, Kenji Koide, Amedeo Cesta, Satoshi Hoshino, Jun Miura, Matteo Salv`a and Emanuele Menegatti
• A Framework to Study Autonomous Driving User Acceptance in the Wild
• Alessandro Gabrielli, Simone Mentasti, Gabriel Esteban Manzoni, Ste- fano Arrigoni, Federico Cheli and Matteo Matteucci
• Probabilistic Collision Constraint for Motion Planning in Dynamic Environments
• Antony Thomas, Fulvio Mastrogiovanni and Marco Baglietto
• Human-following Control in Furrow for Agricultural Support Robot
• Ayanori Yorozu, Genya Ishigami and Masaki Takahashi
• Autonomous Off-Road Navigation using Near-Feature-Based World Knowledge Incorporation on the Example of Forest Path Detection
• Patrick Wolf, Axel Vierling, Thorsten Ropertz, Simon Velden, Carlos Guzman and Karsten Berns
• Learning to Drive Fast on a DuckieTown Highway
• Thomas Wiggers and Arnoud Visser
• End-to-end learning of autonomous vehicle lateral control via MPC training
• Simone Mentasti, Mattia Bersani, Stefano Arrigoni, Matteo Matteucci and Federico Cheli
• End-to-end Imitation Learning for Autonomous Vehicle Steering on a Single-Camera Stream
• Thomas van Orden and Arnoud Visser
• Application Sensorized Compliant Robot Gripper for Estimating the Cooking Time of Boil-Cooked Vegetables
• Grzegorz Sochacki, Josie Hughes and Fumiya Iida
• A Study On Constraint-free Vital Sign Measurement Using A Millimeter Wave Sensor In Home Environment
• Shumpei Nakamura, Huang Shaoying and Wenwei Yu
• Development of a Medication-taking Behavior Monitoring System Using Depth Sensor
• Rikuto Osawa, Shao Ying Huang and Wenwei Yu
• Developing a collaborative robotic dishwasher cell system for restaurantsWingsum Lo, Chihiro Yamamoto, Suraj Prakash Pattar, Koichi Tsukamoto, Shizuka Takahashi, Tetsuya Sawanobori and Ikuo Mizuuchi
• Iterative Improvement for the Heterogeneous Robotic Order Fulfillment Problem Using Simulated Annealing
• Wang Hanfu and Chen Weidong
• Robotic cooking through pose extraction from human natural cooking
• using OpenPose Dylan Danno, Simon Hauser and Fumiya Iida
• Multiple Object Detection and Segmentation for Automated Removal in Additive Manufacturing with Service Robots
• Pascal Becker, Anastasiia Maklashevskikh, Arne Roennau and Ruediger Dillmann
• Determination of posture comfort zones for robot-human handover tasks .
• Oliver Rettig, Marcus Strand and Silvan Muller
• Biomimetic Robots A Simulation Study For Evaluating The Role Of Pre-tensioned Springs In 3 Pneumatic Artificial Muscle Driven Joint Mechanisms With Sliding Mode Controllers
• Zhou Zhongchao, Wang Yuanyuan and Wenwei Yu
• Effect of Tilted Ground on Muscle Activity in Human Sit-to-Stand Motion: Preliminary Result
• Kazunori Yoshida, Qi An, Hiroshi Yamakawa, Yusuke Tamura, Atsushi Yamashita and Hajime Asama
• In-hand Object Recognition for Sensorized Soft Hand
• May Khin, Jin Huat Low, Marcelo Ang and Chen-Hua Yeow
• Scaffolded Learning of In-place Trotting Gait for a Quadruped Robot with Bayesian Optimization
• Keyan Zhai, Chu'An Li and Andre Rosendo
• GradNet: A Viscosity Gradient Approach to Achieve Dexterity in Soft Pneumatic Actuators
• Parthsarthi Rawat, Tanay Misra, Khin Phone May, Marcelo H ANG Jr, Raye Chen-Hua Yeow and Santanu Mitra
• How to tune Humanoid Walking Parameters for better Performance
• Antonio D'Angelo and Enrico Pagello
• Machine Learning TridentNet: A Conditional Generative Model for Dynamic Trajectory Generation.
• David Paz, Hengyuan Zhang and Henrik Christensen
• Adaptive Eligibility Traces for Online Deep Reinforcement Learning
• Taisuke Kobayashi
• Ensemble of LSTMs and feature selection for human action prediction
• Tomislav Petkovic, Luka Petrovic, Ivan Markovic and Ivan Petrovic
• Control Analysis of Exploration in Swarm Robotic Systems
• Minyoung Jeong, John Harwell and Maria Gini
• Reinforcement Learning at the Cognitive Level in a Belief, Desire, Intention UAS Agent
• David Sacharny, Thomas Henderson, Michael Cline and Ben Russon
• Action Feasibility Learning with Cell-based Multi-Object Representation for Task and Motion Planning
• Junsu Kang, Wan Kyun Chung and Keehoon Kim
• Improved Driving Stability of Segway using two Serial Elastic Actuators .
• Jinuk Bang and Jangmyung Lee
• Optimal Grasping Control System For Performing Precision Indirect Teaching of Robot Hand
• Seongho Jin, Jonghak Lee and Jangmyung Lee
• Introduction of damping control for obstacle avoidance in direct-contact cobotics operations
• Alexandre Huart, Masaki Takahashi and Ayanori Yorozu
• Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features
• Wanyu Ma, Jihong Zhu and David Navarro-Alarcon
• Robotic Arm Control and Task Training through Deep Reinforcement Learning
• Andrea Franceschetti, Elisa Tosello, Nicola Castaman and Stefano Ghi- doni
• A marker based optical measurement procedure to analyse robot arm movements and its application to improve accuracy of industrial robots.
• Oliver Rettig, Silvan Muller and Marcus Strand
• A Planning Domain Definition Language Generator, Interpreter, and Knowledge Base for Efficient Automated Planning
• Elisa Tosello, Luca Tagliapietra, Enrico Pagello and Emanuele Menegatti
• Weighted Shared-Autonomy with Assistance-to-Target and Collision Avoidance for Intelligent Assistive Robotics
• Stefano Tortora, Roberto Sassi, Ruggero Carli and Emanuele Menegatti
• Automatic Grasp Pose Generation for Parallel Jaw Grippers
• Kilian Kleeberger, Florian Roth, Richard Bormann and Marco Huber
• Simulation and Control of Deformable Autonomous Airships in Turbulent Wind
• Eric Price, Yu Tang Liu, Michael J. Black and Aamir Ahmad
• Computer Vision Visualization of Dump Truck and Excavator in Bird's-eye View by Fisheye Cameras and 3D Range Sensor
• Yuta Sugasawa, Shota Chikushi, Ren Komatsu, Jun Younes Louhi Kasa- hara, Sarthak Pathak, Ryosuke Yajima, Shunsuke Hamasaki, Keiji Na- gatani, Takumi Chiba, Kazuhiro Chayama, Atsushi Yamashita and Ha- jime Asama
• Dynamic Object Removal from Unpaired Images for Agricultural Autonomous Robots
• Hiroyasu Akada and Masaki Takahashi
• Future Image Prediction for Mobile Robot Navigation: Front-facing Camera versus Omni-directional Camera
• Yu Ishihara and Masaki Takahashi
• Improving Embedded Convolutional Object Detectors Through Low-res Training
• Qian Shi, Jiahui Zhu, Zhonglin Nian and Andre Rosendo
• Fusion of Radar- and Lidar-Data for Object-Tracking-Applications at Feature Level
• Maximilian Lindinger, Marcus Strand, Sebastian Schwarzkopf, Matthias Honal and Raphael Engesser
• Learning to Segment Human Body Parts with Synthetically Trained Deep Convolutional Networks
• Alessandro Saviolo, Matteo Bonotto, Daniele Evangelista, Marco Im- peroli, Jacopo Lazzaro, Emanuele Menegatti and Alberto Pretto
• Detection and Classification of defects in plastic components using a deep learning approach
• Marco Mameli, Marina Paolanti, Adriano Mancini, Emanuele Fron- toni and Primo Zingaretti.
• (source: Nielsen Book Data)

This book presents the latest advances and research achievements in the fields of autonomous robots and intelligent systems, presented at the IAS-16 conference, conducted virtually in Singapore, from 22 to 25 June 2021. IAS is a common platform for an exchange and sharing of ideas among the international scientific research and technical community on some of the main trends of robotics and autonomous systems: navigation, machine learning, computer vision, control, and robot design-as well as a wide range of applications. IAS-16 reflects the rise of machine learning and deep learning developments in the robotics field, as employed in a variety of applications and systems. All contributions were selected using a rigorous peer-reviewed process to ensure their scientific quality. Despite the challenge of organising a conference during a pandemic, the IAS biennial conference remains an essential venue for the robotics and autonomous systems community ever since its inception in 1986. Chapters 46 of this book is available open access under a CC BY 4.0 license at link.springer.com.
(source: Nielsen Book Data)

• Sensing for Navigation.- Path Planning and Localization.- Theory and Methods for SLAM.- Offroad Vehicles.- Multi-Robot Systems.- Robot Vision.- Human-Robot Interaction.- Medical Robot Applications.- Robot Control and Actuation.- Robot Design.- Industrial Applications.
• (source: Nielsen Book Data)

This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences commenced in 1986 and represents a premiere event in robotics.
(source: Nielsen Book Data)

• Introduction. Economic Dispatch. Unit Commitment. Hydrothermal Scheduling. Optimal Power Flow. Reactive Optimal Power Dispatch. Available Transfer Capability. Appendix A: Mathematical Model Derivations. Appendix B: Data of Example Systems. Appendix C: Results of Examples. Appendix D: Tips for Programming In Matlab.
• (source: Nielsen Book Data)

• Introduction: Importance of Power System Optimization. Artificial Intelligence as a New Trend for Optimization Problems. Artificial Intelligence Applications in Power Systems. Overview of the Book. References. Economic Dispatch: Introduction. Generator Incremental Cost Curve. Economic Dispatch Problem Formulation without Loss. Economic Dispatch Considering Transmission Loss. Economic Dispatch with Ramp Rate Constraint. Fuel Constrained Economic Dispatch. Economic Dispatch Considering Emission. Economic Dispatch with Transmission Constraint. Economic Dispatch with Non-smooth Cost Functions. Combined Heat and Power Economic Dispatch. Hydrothermal Economic Dispatch. Optimal Power Dispatch in Competitive Electricity Supply Industry. Summary. Problems. References. Unit Commitment: Introduction. Unit Commitment Problem Formulation. Unit Commitment Solution Methods. Constrained Unit Commitment. Security Constrained Unit Commitment. Priced-Based Unit Commitment. Summary. Problems. References. Hydrothermal Scheduling: Introduction. Hydroelectric Plants Model. Hydrothermal Scheduling Formulation. Hydro Thermal Scheduling Solution Methods. Hydro Units in Series. Pumped Storage Hydro Plants. Problem Formulation for Hydrothermal Scheduling for both Hydro Pumped Storage Hydro Plants. Solution Methods for Hydrothermal Scheduling including Pumped Storage Hydro Plants. Summary. Problems. References. Optimal Power Flow: Introduction. Optimal Power Flow Problem Formulation. Optimal Real Power Dispatch with Network Limit Constraints. Neural Network Application to Optimal Power Flow. Particle Swarm Optimization for Optimal Power Flow. Summary. Problems. References. Reactive Optimal Power Dispatch: Introduction. Reactive Power Essence in Power Systems. Conventional Optimal Reactive Power Dispatch. Optimal Reactive Power Dispatch under Deregulated Electricity Market. TVAC-PSO Based Optimal Reactive Power Dispatch under Deregulated Electricity Market. Summary. Problems. References. Available Transfer Capability: Introduction. Transmission Transfer Capability Concepts. Available Transfer Capability Principles. Available Transfer. Capability Definition and Determination. Methodologies to Calculate ATC. Available Transfer Capability Calculation. Calculation of Total Transfer Capability by Evolutionary Programming. Total Transfer Capability Enhancement using Hybrid. Evolutionary Algorithm. Optimal Placement of Multi-Type FACTS Devices for ATC Enhancement Using HEA. Summary. Problems. References. Appendix A: Mathematical Model Derivations Appendix B: Data of Example Systems Appendix C: Results of Examples Appendix D: Tips for Programming In Matlab.
• (source: Nielsen Book Data)

With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also useful for those who are interested in using artificial intelligence in power system optimization.
(source: Nielsen Book Data)
With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems.
(source: Nielsen Book Data)

• Intelligent Control.- Optimization of Interval Type-2 Fuzzy Logic Controllers for a Perturbed Autonomous Wheeled Mobile Robot Using Genetic Algorithms.- Fuzzy Control for Output Regulation of a Servomechanism with Backlash.- Stability on Type-1 and Type-2 Fuzzy Logic Systems.- Comparative Study of Type-1 and Type-2 Fuzzy Systems Optimized by Hierarchical Genetic Algorithms.- Comparison between Ant Colony and Genetic Algorithms for Fuzzy System Optimization.- Pattern Recognition.- Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and Its Optimization with Genetic Algorithms.- Interval Type-2 Fuzzy Logic for Module Relevance Estimation in Sugeno Integration of Modular Neural Networks.- Optimization of Response Integration with Fuzzy Logic in Ensemble Neural Networks Using Genetic Algorithms.- Optimization of Modular Neural Network, Using Genetic Algorithms: The Case of Face and Voice Recognition.- A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuzzy Logic.- Intelligent Agents and Social Systems.- A Hybrid Model Based on a Cellular Automata and Fuzzy Logic to Simulate the Population Dynamics.- Soft Margin Training for Associative Memories: Application to Fault Diagnosis in Fossil Electric Power Plants.- Social Systems Simulation Person Modeling as Systemic Constructivist Approach.- Modeling and Simulation by Petri Networks of a Fault Tolerant Agent Node.- Fuzzy Agents.- Hardware Implementations.- Design and Simulation of the Fuzzification Stage through the Xilinx System Generator.- High Performance Parallel Programming of a GA Using Multi-core Technology.- Scalability Potential of Multi-core Architecture in a Neuro-Fuzzy System.- Methodology to Test and Validate a VHDL Inference Engine through the Xilinx System Generator.- Modeling and Simulation of the Defuzzification Stage Using Xilinx System Generator and Simulink.- Modeling, Simulation and Optimization.- A New Evolutionary Method Combining Particle Swarm Optimization and Genetic Algorithms Using Fuzzy Logic.- A Hybrid Learning Algorithm for Interval Type-2 Fuzzy Neural Networks: The Case of Time Series Prediction.- Optimization of Artificial Neural Network Architectures for Time Series Prediction Using Parallel Genetic Algorithms.- Optimized Algorithm of Discovering Functional Dependencies with Degrees of Satisfaction Based on Attribute Pre-scanning Operation.- A Fuzzy Symbolic Representation for Intelligent Reservoir Well Logs Interpretation.- How to Solve a System of Linear Equations with Fuzzy Numbers.- Design and Implementation of a Hybrid Fuzzy Controller Using VHDL.
• (source: Nielsen Book Data)

We describe in this book, new methods and applications of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary al- rithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of intelligent control, which are basically papers that use hybrid systems to solve particular problems of control. The second part contains papers with the main theme of pattern recognition, which are basically papers using soft computing techniques for achieving pattern recognition in different applications. The third part contains papers with the themes of intelligent agents and social systems, which are papers that apply the ideas of agents and social behavior to solve real-world problems. The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.
(source: Nielsen Book Data)

• New Approaches in Intelligent Control-Techniques, Methodologies and Applications-.- Design of Fuzzy Supervisor-based Adaptive Process Control Systems.- Intelligent Carpooling System. A Case Study for Bacau Metropolitan Area.- Naval Intelligent Authentication and Support through Randomization and Transformative Search.- Big Data Approach in an ICT Agriculture Application.- Intelligent Control Systems and Applications on Smart Grids.- Control Through Genetic Algorithms.- Knowledge-Based Intelligent Process Control.- Ciphering of Cloud Computing Environment Based New Intelligent Quantum Service.- Paraconsistent Logics and Applications.- Annotated Logics and Intelligent Control.- Paraconsistent Annotated Logic Program EVALPSN and its Application to Intelligent Control.
• (source: Nielsen Book Data)

This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.
(source: Nielsen Book Data)

The emergence of highly promising and potent technologies has enabled the transition of ordinary objects into smart artifacts-providing wider connectivity of digitized entities that can facilitate the building of connected cities. This book provides readers with a solid foundation on the latest technologies and tools required to develop and enhance.