Advances in intelligent robotics and collaborative automation / / editors, Richard Duro, Yuriy Kondratenko.

• Author: IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications
• TeilnehmendeR: Duro, Richard,; Kondratenko, Yuriy,; IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (2013 : Berlin, Germany)
• Place / Publishing House: Aalborg, Denmark : : River Publishers,, 2015.; ©2015
• Year of Publication: 2015
• Edition: 1st ed.
• Language: English
• Series: River Publishers Series in Automation, Control and Robotics ; Volume 1
• Physical Description: 1 online resource (363 pages) :; illustrations (some color), charts, photographs, graphs, tables.

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area.

Table of Contents

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.