Microprocessors in Robotic and Manufacturing Systems

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S.G. Tzafestas
Springer Science & Business Media, 31 окт. 1991 г. - Всего страниц: 411
Microprocessors play a dominant role in computer technology and have contributed uniquely in the development of many new concepts and design techniques for modem industrial systems. This contribution is excessively high in the area of robotic and manufacturing systems. However, it is the editor's feeling that a reference book describing this contribution in a cohesive way and covering the major hardware and software issues is lacking. The purpose of this book is exactly to fill in this gap through the collection and presentation of the experience of a number of experts and professionals working in different academic and industrial environments. The book is divided in three parts. Part 1 involves the first four chapters and deals with the utilization of microprocessors and digital signal processors ( DSPs ) for the computation of robot dynamics. The emphasis here is on parallel computation with particular problems attacked being task granularity, task allocation/scheduling and communication issues. Chapter I, by Zheng and Hemami, is concerned with the real-time multiprocessor computation of torques in robot control systems via the Newton-Euler equations. This reduces substantially the height of the evaluation tree which leads to more effective parallel processing. Chapter 2, by D'Hollander, examines thoroughly the automatic scheduling of the Newton-Euler inverse dynamic equations. The automatic program decomposition and scheduling techniques developed are embedded in a tool used to generate multiprocessor schedules from a high-level language program.
 

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Содержание

COMPUTATION OP ROBOT DYNAMICS BY A MULTIPROCESSOR SCHEME
2
II TreeHeight Reduction by NewtonEuler State Space Equations
2
III The Multiprocessor System and the Task Allocation
2
IV Performance Evaluation
22
V Parallel Processing for a Two Link Robot System
24
VI Conclusion
27
REFERENCES
29
AUTOMATIC SCHEDULING OF THE NEWTONEULER INVERSE DYNAMICS
31
8 CONCLUSIONS
233
9 REFERENCES
234
NEURAL NETWORKS AND ROBOT VISION
237
2 Neural Networks Operation
238
3 The Linear Pattern Associator
239
4 The Nonlinear Multilayered Pattern Associator
242
5 The Auto Associator
249
6 Constraint Satisfaction Network
251

2 Task Granularity and Communication Overhead
32
3 The NewtonEuler Inverse Dynamics
35
the LEM Analyzer
37
5 Parallel Execution
39
6 Conclusion
45
References
46
NUMERICAL APPLICATIONS OP DSPs IN ROBOTIC COMPUTATIONS
49
2 A Survey of the Main Characteristics of DSPs
52
3 Numerical Applications in Robotic Computations
61
4 Conclusions
75
PARALLEL PROCESSING OF ROBOT CONTROL AND SIMULATION
79
2 PARALLEL PROCESSING OF ROBOTARM CONTROL COMPUTATION
80
3PARALLEL PROCESSING OF ROBOT DYNAMICS SIMULATION
92
4Summary and Future Directions
98
ROBOTIC CONTROL AND VISION
101
MICROPROCESSORBASED CONTROLLERS FOR ROBOTIC MANIPULATORS
103
2 SURVEY OF MICROPROCESSORBASED CONTROLLERS
104
3 TECHNIQUES TO IMPROVE MICROPROCESSORBASED CONTROLLER IMPLEMENTATION
109
4 CONCLUSIONS
120
DESIGN ASPECTS OF A ROBOT COORDINATED BY A DESKTOP COMPUTER
131
2 The supervisory system
132
4 Polynomial fitting
139
5 Implementing the difference equations
141
6 Axis command and coordination
143
7 Implementing the position control loop
147
8 Priority of operations in the axis controller
150
9 Conclusion
152
A PC SIMULATION PROGRAM FOR COMPARING PERFORMANCES OF ROBOT CONTROL ALGORITHMS
153
2 Trajectory generation
155
3 Robot Control
159
4 ROBOT DYNAMICS
162
5 Some Control Algorithms
168
6 Conclusions
173
REFERENCES
174
COLLISION STRATEGIES FOR ROBOT RETREAT AND RESISTANCE
177
2 PreCollision Visual Sensing
178
3 PostCollision Tactile Sensing
201
41 THE CONTROLLER STRUCTURE
205
5 Four Link Biped
207
6 Discussion and Conclusions
213
A DISTRIBUTED CONTROL NETWORK FOR SENSORY ROBOTICS
217
2 DISTRIBUTED SYSTEM ARCHITECTURE
219
3 MODELLING THE ENVIRONMENT
220
4 VISION SYSTEM
221
5 MANIPULATOR GRIPPER AND ASSOCIATED SENSORS
227
6 SENSOR DATA INTEGRATION
231
7 SOFTWARE CONSIDERATIONS
232
7 Competitive Learning Model
253
8 Neural Networks as Parallel Distributed Processing Systems
255
9 Conclusion
256
MANUFACTURING SYSTEMS
259
MICROPROCESSORS IN DATA ACQUISITION SYSTEMS FOR PROCESS CONTROL
261
2 PROCESS CONTROL
270
3 INTEGRATIONAUTOMATION WITH MICROPROCESSOR BASED SYSTEMS
274
4 REFERENCES
277
DESIGN AND ANALYSIS OF A MODULAR CNC SYSTEM
279
1 Introduction
280
2 Physical Components of the CNC Milling Machine
282
3 Transfer Functions of the Feed Drive Control System
283
4 State Space Modelling of the Feed Drive Control System
290
5 Experimental Verification of the Feed Drive Servo Model
294
6 Time Domain Simulation of Contouring Errors
299
7 Conclusion
309
COMPUTER PROGRAMMABLE CONTROL OF A FLEXIBLE MANUFACTURING CELL
311
2 Cell Functional Requirements
312
3 Structural Requirements
314
4 Study and Realization
320
5 Conclusion
332
ROBOT AND PLC SUPPORT SYSTEM BASED ON FIBER OPTIC MAP NETWORK
335
2 LOCAL AREA NETWORK SELECTION CRITERIA
337
3 NETWORK DESIGN
338
4 SUPPORT APPLICATION SOFTWARES
340
5 CONCLUSIONS AND RECOMMENDATIONS
350
EXPERIMENTAL RESULTS OF PARAMETER IDENTIFICATION AND NONLINEAR CONTROL ON A PM STEPPER MOTOR
353
2 Feedback Linearization Controller
354
3 Model Validation and Parameter Identification
358
4 Experimental Set Up and Results
360
5 Future Research
366
References
367
DIGITAL SIGNAL PROCESSOR IMPLEMENTATION OF A KALMAN FILTER FOR DISK DRIVE HEAD POSITIONING MECHANISM
369
2 THE HEADPOSITIONING ACTUATOR
370
3 KALMAN FILTER DESIGN
373
4 Kalman Filter Implementation
376
5 CONCLUSION
382
6 ACKNOWLEDGEMENTS
383
SIMULATION ANALYSIS OF FLEXIBLE MANUFACTURING SYSTEMS USING RENSAM
385
INTRODUCTION
386
COMPANY C
388
RENSAM RESULTS
392
SUMMARY
396
REFERENCES
402
AUTHOR INDEX
403
SUBJECT INDEX
405
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Стр. 383 - This material is based upon work supported under a National Science Foundation Graduate Research Fellowship.

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