Cover -- Half Title - Advances in Intelligent Roboticsand Collaborative Automation -- Series Page - RIVER PUBLISHERS SERIES IN AUTOMATION,CONTROLAND ROBOTICS -- Title Page - Advances in Intelligent Roboticsand Collaborative Automation -- Copy Right Page -- Contents -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- Chapetr 1 - A Modular Architecture for DevelopingRobots for Industrial Applications -- Abstract -- 1.1 Introduction -- 1.2 Main Characteristics for Industrial Operation andDesign Decisions -- 1.3 Implementation of a Heterogeneous ModularArchitecture Prototype -- 1.3.1 Actuator Modules -- 1.3.1.1 Slider module -- 1.3.1.2 Telescopic module -- 1.3.1.3 Rotational module -- 1.3.1.4 Hinge module -- 1.3.2 Connection Mechanism -- 1.3.3 Energy -- 1.3.4 Sensors -- 1.3.5 Communications -- 1.3.6 Control -- 1.4 Some Configurations for Practical Applications -- 1.4.1 Manipulators -- 1.4.2 Climber andWalker Robots -- 1.5 Towards Industrial Applications -- 1.6 Conclusions -- References -- Chapter 2 - The Dynamic Characteristics of aManipulator with Parallel KinematicStructure Based on Experimental Data -- Abstract -- 2.1 Introduction -- 2.2 Purpose and Task of Research -- 2.3 Algorithm for the Structural Identification of theMultivariable Dynamic Object with the Help of theComplete Data -- 2.4 Algorithm for the Structural Identification of theMultivariable Dynamic Object with the Help ofIncomplete Data -- 2.5 The Dynamics of the Mechanism with a ParallelStructure Obtained by Means of the Complete DataIdentification -- 2.6 The Dynamics of the Mechanism with a ParallelStructure Obtained by Means of the IncompleteData Identification -- 2.7 Verification of the Structural Identification Results -- 2.8 Conclusions -- References -- Chapter 3 - An Autonomous Scale Ship Model forParametric Rolling Towing Tank Testing -- Abstract.

3.1 Introduction -- 3.2 System Architecture -- 3.2.1 Data Acquisition -- 3.2.2 Software Systems -- 3.2.3 Speed Control -- 3.2.4 Track-Keeping Control -- 3.2.5 Other Components -- 3.3 Testing -- 3.3.1 Prediction System -- 3.3.2 Prevention System -- 3.3.3 Towing Tank Tests and Results -- 3.3.3.1 Mathematical model validation -- 3.3.3.2 Validation of stability diagrams -- 3.3.3.3 Prediction system tests -- 3.4 Conclusions and FutureWork -- References -- Chapter 4 - Autonomous Knowledge Discovery Basedon Artificial Curiosity-Driven Learningby Interaction -- Abstract -- 4.1 Introduction -- 4.2 Proposed System and Role of Curiosity -- 4.2.1 Interpretation from Observation -- 4.2.2 Search for the Most Coherent Interpretation -- 4.2.3 Human-Robot Interaction -- 4.3 Validation Results by Simulation -- 4.4 Implementation on Real Robot and Validation Results -- 4.4.1 Implementation -- 4.4.2 Validation Results -- 4.5 Conclusions -- References -- Chapter 5 - Information Technology for InteractiveRobot Task Training ThroughDemonstration of Movement1 -- Abstract -- 5.1 Introduction -- 5.2 Conception and Principles of Motion Modeling -- 5.2.1 Generalized Model of Motion -- 5.2.2 Algorithm for Robot Task Training by Demonstration -- 5.2.3 Algorithm for Motion Reproduction after Task Training byDemonstration -- 5.2.4 Verification of Results for the Task of Training theTelecontrolled (Remote Controlled) Robot -- 5.2.5 Major Advantages of Task Training by Demonstration -- 5.3 Algorithms and Models for Teaching Movements -- 5.3.1 Task Training by Demonstration of Movement amongthe Objects of the Environment -- 5.3.2 Basic Algorithms for RobotTaskTraining by Demonstration -- 5.3.3 Training Algorithm for the Environmental Survey Motion -- 5.3.4 Training Algorithm for Grabbing a Single Object -- 5.3.5 Special Features of the Algorithm for Reproduction ofMovements.

5.3.6 Some Results of Experimental Studies -- 5.3.7 Overview of the Environment for Task Training byDemonstration of the Movements of the Human Head -- 5.3.8 Training the Robot to Grab Objects by Demonstration ofOperator Hand Movements -- 5.4 Conclusions -- References -- Chapter 6 - A Multi-Agent Reinforcement LearningApproach for the Efficient Controlof Mobile Robots -- Abstract -- 6.1 Introduction -- 6.2 Holonic Homogenous Multi-Agent Systems -- 6.2.1 Holonic, Multi-Agent Systems -- 6.2.2 Homogenous, Multi-Agent Systems -- 6.2.3 Approach to Commitment and Coordination in H2 MAS -- 6.2.4 Learning to Coordinate Through Interaction -- 6.3 Vehicle Steering Module -- 6.4 A Decomposition of Mobile Platform -- 6.5 The Robot Control System Learning -- 6.5.1 Learning of the Turning of a Module-Agent -- 6.5.1.1 Simulation -- 6.5.1.2 Verification -- 6.5.2 Learning of the Turning of a Module-Agent -- 6.5.2.1 Simulation -- 6.5.2.2 Verification -- 6.6 Conclusions -- References -- Chapter 7 - Underwater Robot Intelligent Control Basedon Multilayer Neural Network -- Abstract -- 7.1 Introduction -- 7.2 Underwater Robot Model -- 7.3 Intelligent NN Controller and Learning AlgorithmDerivation -- 7.4 Simulation Results of the Intelligent NN Controller -- 7.5 Modification of NN Control -- 7.6 Conclusions -- Acknowledgement -- References -- Chapter 8 - Advanced Trends in Design of SlipDisplacement Sensors for Intelligent Robots -- Abstract -- 8.1 Introduction -- 8.2 Analysis of Robot Task Solving Based on SlipDisplacement Signals Detection -- 8.3 Analysis of Methods for Slip Displacement SensorsDesign -- 8.4 Mathematical Model of Magnetic Slip DisplacementSensor -- 8.4.1 SDS Based on "Permanent Magnet/Hall Sensor" SensitiveElement and Its Mathematical Model -- 8.4.2 Simulation Results -- 8.5 Advanced Approaches for Increasing the Efficiencyof Slip Displacement Sensors.

8.6 Advances in Development of Smart Grippers forIntelligent Robots -- 8.6.1 Self-Clamping Grippers of Intelligent Robots -- 8.6.2 Slip Displacement Signal Processing in Real Time -- 8.7 Conclusions -- References -- Chapter 9 - Distributed Data Acquisition and ControlSystems for a Sized Autonomous Vehicle -- Abstract -- 9.1 Introduction -- 9.2 The Testing Environment -- 9.3 Description of the System -- 9.4 Lane Detection -- 9.4.1 In-Range Filter -- 9.4.2 Hough-Transformation -- 9.4.3 Lane Marks -- 9.4.4 Polynomial -- 9.4.5 Driving Lane -- 9.4.6 Stop Line -- 9.4.7 Coordinate Transformation -- 9.5 Control of the Vehicle -- 9.6 Results -- 9.7 Conclusions -- References -- Chapter 10 - Polymetric Sensing in Intelligent Systems -- Abstract -- 10.1 Topicality of Polymetric Sensing -- 10.2 Advanced Perception Components of IntelligentSystems or Robots -- 10.2.1 Comparison of the Basics of Classical and PolymetricSensing -- 10.2.2 Advanced Structure of Multi-Agent Intelligent Systems -- 10.3 Practical Example of Polymetric Sensing -- 10.3.1 Adding the Time Scale -- 10.3.2 Adding the Information about the Velocity of theElectromagneticWave -- 10.4 Efficiency of Industrial Polymetric Systems -- 10.4.1 Naval Application -- 10.4.1.1 Sensory monitoring agency SMA -- 10.4.1.2 Information Environment Agency INE -- 10.4.1.3 Operator Interface Agency OPI -- 10.4.1.4 Advantages of the polymetric sensing -- 10.4.1.5 Floating dock operation control system -- 10.4.1.6 Onshore applications -- 10.4.1.7 Special applications -- 10.5 Conclusions -- References -- Chapter 11 - Design and Implementation of WirelessSensor Network Based on MultilevelFemtocells for Home Monitoring -- Abstract -- 11.1 Introduction -- 11.2 Network Architecture and Femtocell Structure -- 11.2.1 Body Sensor Network -- 11.2.2 Ambient Sensor Network -- 11.2.3 Emergency Sensor Network.

11.2.4 Higher-level Architecture and Functional Overview -- 11.3 Data Processing -- 11.4 Experimental Results -- 11.5 Conclusion -- References -- Chapter 12 - Common Framework Modelfor Multi-Purpose Underwater DataCollection Devices Deployed with RemotelyOperated Vehicles -- Abstract -- 12.1 Introduction -- 12.2 Research Challenges -- 12.2.1 Power Supply -- 12.2.2 Communications -- 12.2.3 Maintenance -- 12.2.4 Law and Finance -- 12.2.5 Possible Applications -- 12.3 Mathematical Model -- 12.3.1 System Definition -- 12.3.2 Actuator Definition -- 12.3.3 Sensor Definition -- 12.4 ROV -- 12.4.1 ROV Manipulator Systems -- 12.4.2 Types of Offshore Constructions -- 12.5 ROV Simulator -- 12.6 Common Modular Framework -- 12.7 Conclusions -- References -- Chapter 13 - M2M in Agriculture - Business Modelsand Security Issues -- Abstract -- 13.1 Introduction -- 13.2 RelatedWork -- 13.3 Communication and Standardization -- 13.4 Business Cases -- 13.4.1 Process Transparency (PT) -- 13.4.2 Operations Data Acquisition (ODA) -- 13.4.3 Remote Software Update (RSU) -- 13.5 Business Models -- 13.6 Economic Analysis -- 13.7 Communication Security -- 13.7.1 CA -- 13.7.2 Communicating On-the-Go -- 13.7.3 Covering Dead Spots -- 13.7.4 Securing WLAN Infrastructures -- 13.7.5 Firmware Update -- 13.8 Resume -- 13.9 Acknowledgement -- References -- Index -- Editor's Biographies -- Author's Biographies.