Web-Based Control and Robotics Education

1. Auflage 2009
ISBN: 978-90-481-2505-0
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 346 Seiten

For the things we have to learn before we can do them, we learn by doing them. Aristotle Teaching should be such that what is offered is perceived as a valuable gift and not as a hard duty. Albert Einstein The second most important job in the world, second only to being a good parent, is being a good teacher. S.G. Ellis The fast technological changes and the resulting shifts of market conditions require the development and use of educational methodologies and opportunities with moderate economic demands. Currently, there is an increasing number of edu- tional institutes that respond to this challenge through the creation and adoption of distance education programs in which the teachers and students are separated by physical distance. It has been verified in many cases that, with the proper methods and tools, teaching and learning at a distance can be as effective as traditional fa- to-face instruction. Today, distance education is primarily performed through the Internet, which is the biggest and most powerful computer network of the World, and the World Wide Web (WWW), which is an effective front-end to the Internet and allows the Internet users to uniformly access a large repertory of resources (text, data, images, sound, video, etc.) available on the Internet.

Autoren/Hrsg.

Inhaltsverzeichnis

1;Contents;9
2;Contributors;11
3;Outline of the Book;14
4;Acronyms;20
5;Teaching Control and Robotics Using the Web;24
5.1;1.1 Introduction;24
5.2;1.2 Review of the Web-Based Control and Robotics Educational Platforms;26
5.2.1;1.2.1 E-Course/E-Classroom Environments;26
5.2.2;1.2.2 Web-Based Virtual Laboratories;27
5.2.3;1.2.3 Web-Based Remote Laboratories;28
5.3;1.3 Web Telerobotics and Internet Delay;30
5.3.1;1.3.1 General Issues;30
5.3.2;1.3.2 The Quality of Service Model of Communication Networks;32
5.3.3;1.3.3 Internet Delay Modeling and Estimation;34
5.3.3.1;1.3.3.2 The ARIMA Internet Delay Estimation Technique;36
5.4;1.4 General Characteristics of Web-Based Virtual Laboratories;38
5.4.1;1.4.1 General Architecture of VLabs;38
5.4.2;1.4.2 Communication Characteristics;40
5.4.3;1.4.3 Human–Computer Interface Characteristics;42
5.4.4;1.4.4 System Modeling;42
5.5;1.5 General Characteristics of Web-Based Remote Laboratories;43
5.5.1;1.5.1 General Requirements of Remote Labs;43
5.5.2;1.5.2 General Architecture of Remote Labs;44
5.6;1.6 Some Examples;46
5.6.1;1.6.1 Example 1: Internet Delay Estimation;46
5.6.2;1.6.2 Example 2: Effect of Time Delay on Teleoperation;47
5.6.3;1.6.3 Example 3: The Wheel-Driven Robot Lab of the University of Hagen;47
5.6.4;1.6.4 Example 4: The Remote Control Lab (Recolab);48
5.6.5;1.6.5 Example 5: The Distributed Control Lab (DCL);49
5.7;1.7 Concluding Remarks;51
5.8;1.8 Appendix: Software Environments for Developing Web-Based Educational Platforms;51
5.8.1;1.8.1 Web 2.0;51
5.8.2;1.8.2 Matlab;52
5.8.3;1.8.3 LabVIEW;52
5.8.4;1.8.4 VRML;53
5.8.5;1.8.5 Java;53
5.8.6;1.8.6 HTML and HTTP;54
5.8.7;1.8.7 PHP Hypertext Preprocessor;55
5.8.8;1.8.8 CORBA;55
5.9;References;56
6;Control System Design and Analysis Education via the Web;62
6.1;2.1 Introduction;62
6.2;2.2 Ch Control Systems Toolkit;63
6.2.1;2.2.1 Design and Implementation;64
6.2.2;2.2.2 Simple Application Example;65
6.2.3;2.2.3 Extending the Simple Example;66
6.3;2.3 Web Based Control Design and Analysis;69
6.3.1;2.3.1 Web Control Application Example;71
6.4;2.4 Customized Design and Implementation of Web-Based Control Systems;72
6.4.1;2.4.1 Root Locus Web Application Example;73
6.4.1.1;2.4.1.1 Problem Description;73
6.4.1.2;2.4.1.2 Problem Solution;73
6.4.2;2.4.2 Compensator Web Tool Development;78
6.4.2.1;2.4.2.1 The CRequest Class;78
6.4.2.2;2.4.2.2 The CResponse Class;79
6.4.2.3;2.4.2.3 Source Code Example;79
6.5;2.5 Conclusion;81
6.6;References;81
7;Web Based Control Teaching;83
7.1;3.1 Introduction;83
7.2;3.2 Motivation for Web Based Control Teaching;84
7.3;3.3 Virtual Control Design Laboratory;87
7.3.1;3.3.1 Web Sisotool – A Standard MATLAB Web Server (MWS) Application;88
7.3.2;3.3.2 M-file Application;90
7.4;3.4 A DSP-Based Remote Control Laboratory;93
7.4.1;3.4.1 A DSP-Based Remote Control Laboratory;94
7.4.2;3.4.2 RC Oscillator Experiment;96
7.4.2.1;3.4.2.1 Description of the Experiment;96
7.4.3;3.4.3 DC Motor Speed Control Experiment;99
7.4.3.1;3.4.3.1 Experiment Description;99
7.5;3.5 Conclusion;103
7.6;References;103
8;Web-Based Control Education in Matlab;105
8.1;4.1 Introduction;105
8.2;4.2 Standard Solutions;106
8.2.1;4.2.1 The Matlab Web Server;106
8.2.2;4.2.2 Web Applications and Matlab Builders Products;107
8.2.2.1;4.2.2.1 The Matlab Builder for JAVA;108
8.2.2.2;4.2.2.2 The Matlab Builder for .NET;111
8.2.3;4.2.3 Matlab Compiler and CGI Scripts;112
8.3;4.3 Alternative Solutions;112
8.3.1;4.3.1 Matlab Dynamic Data Exchange (DDE);113
8.3.2;4.3.2 The Component Object Model;114
8.3.3;4.3.3 Matlab and Java;116
8.3.3.1;4.3.3.1 Calling Java from Matlab;116
8.3.3.2;4.3.3.2 Calling Matlab from Java;116
8.3.3.2.1;Java Matlab Interface;117
8.3.3.2.2;JMatLink;117
8.3.3.2.3;Java Runtime Class;117
8.3.3.2.4;JNI Wrapper for Matlab’s C Engine;118
8.3.3.2.5;JMatlab/Link;118
8.3.4;4.3.4 Communication via File;119
8.3.5;4.3.5 Communication via TCP/IP;119
8.3.5.1;4.3.5.1 The MathWorks Instrument Control Toolbox;120
8.3.6;4.3.5.2 The TCP/UDP/IP Toolbox;120
8.3.6.1;4.3.5.3 The S-function Block;120
8.4;4.4 Client Applications;121
8.5;4.5 Conclusions;122
8.6;References;123
9;Object-Oriented Modelling of Virtual-Laboratories for Control Education;125
9.1;5.1 Introduction;125
9.2;5.2 Implementation of Virtual-Labs with Batch Interactivity;127
9.3;5.3 Implementation of Virtual-Labs with Runtime Interactivity;128
9.3.1;5.3.1 Virtual-Lab Implementation by Combining the Use of Ejs, Matlab/Simulink and Modelica;129
9.3.2;5.3.2 Virtual-Lab Implementation using VirtualLabBuilder;130
9.4;5.4 Case Study I: Control of a Double-Pipe Heat Exchanger;133
9.4.1;5.4.1 Virtual-Lab Model;133
9.4.2;5.4.2 Composing the Virtual-Lab;135
9.5;5.5 Case Study II: Control of an Industrial Boiler;137
9.5.1;5.5.1 Virtual-Lab Model;138
9.5.2;5.5.2 Composing the Virtual-Lab;138
9.6;5.6 Case Study III: Solar House;140
9.6.1;5.6.1 Virtual-Lab Model;140
9.6.2;5.6.2 Composing the Virtual-Lab;140
9.7;5.7 Conclusions;144
9.8;References;145
10;A Matlab-Based Remote Lab for Control and Robotics Education;148
10.1;6.1 Introduction;148
10.2;6.2 The Automatic Control Telelab;149
10.2.1;6.2.1 ACT Features;149
10.2.2;6.2.2 Teaching Experiences;151
10.3;6.3 ACT Experiments Description;152
10.3.1;6.3.1 Control Experiment;152
10.3.1.1;6.3.1.1 Designing User-Defined Controllers;153
10.3.1.2;6.3.1.2 Running the Experiments;153
10.3.2;6.3.2 Remote System Identification;156
10.3.3;6.3.3 Student Competition Overview;158
10.3.3.1;6.3.3.1 A Competition Session Description;160
10.4;6.4 The ACT Architecture;163
10.5;6.5 The Robotics and Automatic Control Telelab;165
10.5.1;6.5.1 General Architecture;166
10.5.2;6.5.2 Experiments description;167
10.5.2.1;6.5.2.1 Inverse Kinematics Experiment;167
10.5.2.2;6.5.2.2 Visual Servoing Experiment;169
10.5.2.3;6.5.2.3 Future Developments;171
10.6;6.6 Conclusions;171
10.7;References;172
11;Implementation of a Remote Laboratory Accessible Through the Web;173
11.1;7.1 Introduction;173
11.2;7.2 Examples of Existing Virtual Labs;174
11.3;7.3 User Interface;177
11.4;7.4 Software Architecture;178
11.4.1;7.4.1 Basic Details;178
11.4.2;7.4.2 Advanced Details;181
11.5;7.5 Hardware Architecture;182
11.6;7.6 Experiments;184
11.6.1;7.6.1 Ball Balancing Device Experiment;184
11.6.2;7.6.2 Rotating Web Cam Experiment;187
11.7;7.7 Conclusions;188
11.8;References;189
12;Teaching of Robot Control with Remote Experiments;190
12.1;8.1 Introduction;190
12.2;8.2 Educational Strategy;191
12.3;8.3 The DSP-Based Remote Control Laboratory;193
12.4;8.4 Control of a Mechanism with Spring;195
12.4.1;8.4.1 Dynamic Model of the Mechanism with Spring;196
12.4.2;8.4.2 Control Design for the Mechanism with Spring;199
12.4.2.1;8.4.2.1 Cascade Control;199
12.4.2.2;8.4.2.2 PD Control;200
12.4.2.3;8.4.2.3 Computed Torque Control;201
12.4.3;8.4.3 Remote Experiments Using the Mechanism with Spring;203
12.5;8.5 Control of the SCARA Robot;205
12.5.1;8.5.1 The Dynamic Model of the SCARA Robot;205
12.5.2;8.5.2 Control Design for the SCARA Robot;207
12.5.2.1;8.5.2.1 Cascade Control;207
12.5.2.2;8.5.2.2 PD Control;208
12.5.2.3;8.5.2.3 Computed Torque Control;208
12.5.3;8.5.3 Remote Experiments with the SCARA Robot;209
12.6;8.6 Students’ Feedback;209
12.7;8.7 Conclusions;211
12.8;References;212
13;Web-Based Laboratory on Robotics: Remote vs. Virtual Training in Programming Manipulators;214
13.1;9.1 Introduction;214
13.2;9.2 Remote Labs: Literature Survey;216
13.3;9.3 Research Motivation and Objectives;217
13.3.1;9.3.1 Technological Background: Virtual Reality in Telerobotics;218
13.3.1.1;9.3.1.1 Telerobotics: Historical Evolution;218
13.3.1.2;9.3.1.2 Telerobotics and Virtual Reality: Synergy;220
13.3.1.3;9.3.1.3 Web-Based Telerobots;223
13.3.2;9.3.2 Technological and Educational Research Objectives;225
13.4;9.4 Design of a Virtual and Remote Robot Laboratory Platform;227
13.4.1;9.4.1 E-Training Scenarios in Robot Manipulator Programming;227
13.4.2;9.4.2 Platform architecture and Web-Based Graphical User Interface;229
13.4.3;9.4.3 Robot Programming Modes: Virtual Pendant and e-Console;231
13.4.3.1;9.4.3.1 The Virtual Pendant Emulator;232
13.4.3.2;9.4.3.2 E-console: V.+. Robot Programming User Interface;233
13.5;9.5 Pilot Study: Research Methodology and Results;235
13.5.1;9.5.1 Experimental Protocol;235
13.5.2;9.5.2 Experimental Results;237
13.5.3;9.5.3 Analysis of Experimental Results – Discussion;239
13.6;9.6 Conclusion – Future Research Directions;240
13.7;References;243
14;Design and Educational Issues within the UJI Robotics Telelaboratory: A User Interface Approach;245
14.1;10.1 Introduction;245
14.1.1;10.1.1 The Aim of the System;245
14.1.2;10.1.2 A Brief Account of the State of the Art;246
14.2;10.2 System Description – The Architecture;246
14.2.1;10.2.1 Implementation Details;250
14.3;10.3 System Description – The User Interface;252
14.3.1;10.3.1 Using a Web Navigator;253
14.3.2;10.3.2 By Means of a Programming Language;254
14.3.3;10.3.3 Through the Java Interface;255
14.4;10.4 A New Network Protocol: SNRP;257
14.4.1;10.4.1 The SNRP Description;257
14.4.2;10.4.2 Example of a SNRP Library;259
14.5;10.5 Teaching Experiences with the Tele-Laboratory;259
14.5.1;10.5.1 Basic Experiments;260
14.5.1.1;10.5.1.1 SNRP and XML-RPC Experiment;260
14.5.1.2;10.5.1.2 HTTP Experiment;260
14.5.2;10.5.2 Advanced Experiments;261
14.5.2.1;10.5.2.1 Java Interface Experiment;261
14.5.2.2;10.5.2.2 Programming Language Experiment;262
14.6;10.6 Conclusions and Work in Progress;264
14.7;References;265
15;Web-Based Industrial Robot Teleoperation: An Application;266
15.1;11.1 Introduction;266
15.2;11.2 System Architecture;268
15.2.1;11.2.1 The Robot SMART 3-S;269
15.2.2;11.2.2 The C3G 9000 Controller;269
15.2.3;11.2.3 The PC Server;270
15.2.4;11.2.4 The Web Cams;271
15.3;11.3 Teleprogramming and Supervisory Control Functions;271
15.3.1;11.3.1 Shared Autonomy Control;272
15.3.2;11.3.2 Supervisory Control Functions;273
15.3.3;11.3.3 Off-Line VRML Trajectory Simulation;274
15.4;11.4 Software Architecture;275
15.4.1;11.4.1 C3G-9000 Software;275
15.4.2;11.4.2 PC-Server Software;276
15.4.3;11.4.3 PC-Client Software;277
15.5;11.5 Teleoperation User Interface;277
15.5.1;11.5.1 Shared Autonomy;280
15.6;11.6 Conclusions;281
15.7;References;282
16;Teleworkbench: A Teleoperated Platform for Experiments in Multi-robotics;284
16.1;12.1 Introduction;284
16.2;12.2 The Teleworkbench System;285
16.2.1;12.2.1 Teleworkbench Server;287
16.2.2;12.2.2 Video Server;288
16.2.3;12.2.3 WWW Server;288
16.2.4;12.2.4 Teleworkbench Post-experiment Analysis Tool;288
16.2.4.1;12.2.4.1 Visualization Generator;289
16.2.4.1.1;Data Extractor;290
16.2.4.1.2;Scene Generator;291
16.2.4.1.3;MPEG-4 Scene Encoder;291
16.2.4.2;12.2.4.2 Interactive Video as User Interface;292
16.2.5;12.2.5 Teleworkbench Application Programming Interface (API);292
16.2.6;12.2.6 Teleworkbench Graphical User Interface (GUI);293
16.3;12.3 Robot Platform;294
16.3.1;12.3.1 Khepera Minirobot;295
16.3.2;12.3.2 BeBot – HNI Minirobot;295
16.4;12.4 Application Scenarios in Research and Education;295
16.4.1;12.4.1 From Local to Remote Experiment;297
16.4.1.1;12.4.1.1 Web Service Interfaces for Mobile Autonomous Robots;298
16.4.1.2;12.4.1.2 Robot Tele-Programming;298
16.4.2;12.4.2 Batch, Interactive, and Sensor Experiments;299
16.4.3;12.4.3 From Simulator to Real-Robots;301
16.4.3.1;12.4.3.1 Robot Path Planning;303
16.4.4;12.4.4 Robotic Experiment Analysis;304
16.4.4.1;12.4.4.1 Robot Motor Controller;305
16.4.4.2;12.4.4.2 Cooperative Multi-robots;305
16.4.4.3;12.4.4.3 Swarm Robots;306
16.4.4.4;12.4.4.4 Unknown Environment Exploration;308
16.5;12.5 Challenges for a Teleoperated Robotic Laboratory in Research and Education;310
16.6;12.6 Summary and Future Work;311
16.7;References;312
17;Web-Based Control of Mobile Manipulation Platforms via Sensor Fusion;314
17.1;13.1 Introduction;314
17.2;13.2 Prior Work;315
17.3;13.3 Design Specifications;316
17.3.1;13.3.1 Data Acquisition;316
17.3.2;13.3.2 Sensors;316
17.3.2.1;13.3.2.1 Sonar Sensor;317
17.3.2.2;13.3.2.2 Infrared Proximity Sensor;318
17.3.3;13.3.3 Jazzy 1122 Wheelchair;320
17.4;13.4 Applications;321
17.4.1;13.4.1 Manipulability;321
17.4.2;13.4.2 Navigation and Obstacle Avoidance;322
17.4.3;13.4.3 Path Planning and Map Building;323
17.5;13.5 Implementation and Results;325
17.6;13.6 Conclusions and Future Work;327
17.7;References;328
18;Web Based Automated Inspection and Quality Management;330
18.1;14.1 Introduction;330
18.2;14.2 Web-Based AI and QM System – How It Works?;332
18.3;14.3 Literature Review;332
18.4;14.4 System Architecture for AI and QM;334
18.5;14.5 Metrology Hardware – Sensors and Instrumentation;335
18.5.1;14.5.1 Discrete Digital and Analog Sensors;335
18.5.2;14.5.2 Discrete Metrology Instrumentation;336
18.5.3;14.5.3 Vision Systems and Vision Sensors;336
18.5.4;14.5.4 Coordinate Measuring Machines (CMMs);338
18.6;14.6 Metrology Hardware Integration;339
18.6.1;14.6.1 Discrete Digital and Analog Sensor Integration;339
18.6.2;14.6.2 Discrete Metrology Instrumentation Integration;341
18.6.3;14.6.3 Vision System and Vision Sensor Integration;342
18.6.4;14.6.4 CMM Integration;342
18.7;14.7 Control System Integration;343
18.7.1;14.7.1 PLC Based Control;344
18.7.2;14.7.2 Opto 22 Based Control;344
18.7.3;14.7.3 NI – LabView Based Control;344
18.8;14.8 Supervisory System Integration;345
18.8.1;14.8.1 ControlNet™;345
18.8.2;14.8.2 Ethernet;345
18.9;14.9 Enterprise/Management Information System Integration;345
18.10;14.10 Overall System Integration – An Example;346
18.11;14.11 System Safety;347
18.12;14.12 Educational Impact;347
18.13;14.13 Conclusion;348
18.14;References;348
19;Biographies;350
20;Index;359