Control in Robotics and Automation

by Ghosh, B. K.; Xi, Ning; Tarn, Tzyh-Jong

• ISBN13: 9780122818455
• ISBN10: 0122818458
• Format: Hardcover
• Copyright: 1999-03-01
• Publisher: Academic Pr

Summary

Microcomputer technology and micromechanical design have contributed to recent rapid advances in Robotics. Particular advances have been made in sensor technology that allow robotic systems to gather data and react "intelligently" in flexible manufacturing systems. The analysis and recording of the data are vital to controlling the robot. In order to solve problems in control and planning for a Robotic system it is necessary to meet the growing need for the integration of sensors in to the system. Control in Robotics and Automation addresses this need. This book covers integration planning and control based on prior knowledge and real-time sensory information. A new task-oriented approach to sensing, planning and control introduces an event-based method for system design together with task planning and three dimensional modeling in the execution of remote operations. Typical remote systems are teleoperated and provide work efficiencies that are on the order of ten times slower than what is directly achievable by humans. Consequently, the effective integration of automation into teleoperated remote systems offers potential to improve remote system work efficiency. The authors introduce visually guided control systems and study the role of computer vision in autonomously guiding a robot system. * Sensor-Based Planning and Control in an Event-Based Approach * Visually Guided Sensing and Control * Multiple Sensor Fuson in Planning and Control * System Integration and Implementation * Practical Applications

Table of Contents

Preface	ix	(2)
Contributors	xi
Section I INTRODUCTION	1	(56)
1. Sensor-Based Planning and Control for Robotic Systems: An Event-Based Approach	3	(54)
Xi
Tarn
1. Introduction	3	(2)
2. Event-Based Planning and Control	5	(5)
3. Event-Based Motion Planning and Control for a Robot Arm	10	(13)
4. Event-Based Planning and Control for Multirobot Coordination	23	(19)
5. Implementation of Event-Based Planning and Control	42	(9)
6. Conclusions	51	(1)
References	52	(5)
Section II VISUALLY GUIDED SENSING AND CONTROL	57	(88)
2. Observer-Based Visual Servoing	59	(32)
Hashimoto
1. Introduction	60	(2)
2. Mathematical Formulation	62	(3)
3. Jacobians	65	(3)
4. Nonlinear Control Law	68	(8)
5. Linearized Controller	76	(1)
6. Experiments	76	(11)
7. Conclusions	87	(1)
References	88	(3)
3. Using Active Deformable Models in Visual Servoing	91	(24)
Sullivan
Papanikolopoulos
Singh
Pavlidis
1. Introduction	91	(1)
2. Importance of the Visual Servoing Problem	92	(1)
3. Issues	93	(2)
4. Previous Work	95	(1)
5. Proposed Approach	95	(8)
6. The Minnesota Robotic Visual Tracker	103	(2)
7. Experiments	105	(5)
8. Discussion	110	(1)
9. Future Work	111	(1)
10. Conclusions	112	(1)
References	112	(3)
4. Visually Guided Tracking and Manipulation	115	(30)
Lei
Ghosh
1. Introduction	115	(2)
2. Modeling of the Tracking and Grasping System	117	(4)
3. Estimation of the Motion Field of the Reference Point	121	(9)
4. The Control Design for Tracking and Grasping	130	(9)
5. Simulation Results and Discussion	139	(3)
6. Conclusions	142	(1)
References	143	(2)
Section III MULTIPLE SENSOR FUSION IN PLANNING AND CONTROL	145	(98)
5. Complementary Sensor Fusion in Robotic Manipulation	147	(36)
Ghosh
Yu
Xiao
Xi
Tarn
1. Introduction	148	(3)
2. Grasping	151	(18)
3. Tracking an Unknown Trajectory on a Surface	169	(9)
4. Conclusion	178	(1)
References	179	(2)
5. Appendix	181	(2)
6. Feedback Control with Force and Visual Sensor Fusion	183	(34)
Nelson
Khosla
1. Introduction	184	(2)
2. Previous Work	186	(2)
3. Sensor Resolvability	188	(14)
4. Visual Servoing Formulation	202	(2)
5. Vision-Force Servoing	204	(3)
6. Experimental Results	207	(6)
7. Conclusion	213	(1)
References	214	(3)
7. Sensor-Referenced Impact Control in Robotics	217	(26)
Wu
Tarn
Xi
Isidori
1. Introduction	217	(1)
2. History and Background	218	(2)
3. Impact Dynamics	220	(2)
4. Robust Impact Control	222	(4)
5. Switching Control	226	(7)
6. Experiments	233	(2)
7. Summary	235	(5)
References	240	(1)
Suggested Readings	241	(2)
Section IV SYSTEM INTEGRATION, MODELING, AND CONTROLLER DESIGN	243	(68)
8. A Modular Approach to Sensor Integration	245	(24)
Anderson
1. Introduction	245	(1)
2. Terminology	246	(1)
3. The Problem of Algebraic Loops	246	(3)
4. Scattering Theory	249	(3)
5. Applying Scattering Theory to Robot Modules	252	(3)
6. Computing the Jacobian Scattering Operator	255	(3)
7. Discretizing Dynamic Networks	258	(2)
8. Imposing Nonlinear Constraints Using Sensor Feedback	260	(4)
9. Implementation	264	(1)
10. Examples	264	(3)
11. Conclusions	267	(1)
References	267	(2)
9. A Circuit-Theoretic Analysis of Robot Dynamics and Control	269	(16)
Arimoto
1. Introduction	269	(2)
2. Passivity of Robot Dynamics and Nonlinear Position-Dependent Circuits	271	(3)
3. SP-ID Control	274	(1)
4. Adaptability and Learnability	275	(3)
5. Realization of Friction/Gravity-Free Robots	278	(1)
6. Generalization of Impedance Matching to Nonlinear Dynamics	279	(2)
7. Learning as Making Progress Toward Impedance Matching	281	(2)
8. Conclusion	283	(1)
References	283	(2)
10. Sensor-Based Planning and Control in Telerobotics	285	(26)
Hamel
1. Introduction	285	(1)
2. History of Teleoperations and Remote Handling	286	(9)
3. The Notion of Telerobotics	295	(2)
4. Typical Application Domain	297	(3)
5. A Robust Telerobotic Concept	300	(2)
6. Current Research in Integrated D&D Telerobotics	302	(5)
7. Key Remaining Challenges and Summary	307	(1)
References	308	(3)
Section V APPLICATION	311	(108)
11. Automated Integration of Multiple Sensors	313	(34)
Baker
1. Introduction	313	(1)
2. Background	314	(6)
3. Automated MSI System	320	(10)
4. Target Sensor Domains	330	(2)
5. Sensor Anomaly Correction	332	(2)
6. Empirical Evaluation	334	(4)
7. Validation	338	(5)
8. Sumary	343	(1)
References	344	(3)
12. Robotics with Perception and Action Nets	347	(34)
Lee
Ro
1. Introduction	348	(1)
2. Pan Architecture	349	(3)
3. Uncertainty Management	352	(8)
4. Error Monitoring and Recovery	360	(2)
5. Planetary Robotic Science Sampling	362	(3)
6. Simulation	365	(8)
7. Experimentation	373	(4)
8. Conclusion	377	(1)
References	378	(1)
Appendix	379	(2)
13. A Fuzzy Behaviorist Approach to Sensor-Based Reasoning and Robot Navigation	381	(38)
Pin
1. Introduction	381	(3)
2. Fuzzy Behaviorist Approach and Rule Generation for Vehicle Navigation	384	(11)
3. Rule Base Generation Method and Automated System	395	(2)
4. Sample Experimental Results	397	(10)
5. Augmenting the System with Memory and Memory-Processing Behaviors	407	(9)
6. Concluding Remarks	416	(1)
References	417	(2)
Index	419