Kinematic Modeling, Identification, and Control of Robotic Manipulators

Henry W. Stone

ISBN 10: 0898382378 / ISBN 13: 9780898382372

Editore: Springer US, Springer New York Sep 1987, 1987

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Neuware -The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance. The positioning accuracy of commercially-available industrial robotic manipulators depends upon a kinematic model which describes the robot geometry in a parametric form. Manufacturing error in the machining and assembly of manipulators lead to discrepancies between the design parameters and the physical structure. Improving the kinematic perfor mance thus requires the identification of the actual kinematic parameters of each individual robot. The identified kinematic parameters are referred to as the arm signature. Existing robot kinematic models, such as the Denavit-Hartenberg model, are not directly applicable to kinematic parameter identification. In this dissertation we introduce a new kinematic model, called the 5-Model, which is applicable to kinematic parameter identification, and use it as the foundation for our development of a general technique for identifying the kinematic parameters of any robot with rigid links.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch. Codice articolo 9780898382372

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Titolo: Kinematic Modeling, Identification, and ...

Casa editrice: Springer US, Springer New York Sep 1987

Data di pubblicazione: 1987

Legatura: Buch

Condizione: Neu

Descrizione articolo

Riassunto:

The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance. The positioning accuracy of commercially-available industrial robotic manipulators depends upon a kinematic model which describes the robot geometry in a parametric form. Manufacturing error in the machining and assembly of manipulators lead to discrepancies between the design parameters and the physical structure. Improving the kinematic perfor­ mance thus requires the identification of the actual kinematic parameters of each individual robot. The identified kinematic parameters are referred to as the arm signature. Existing robot kinematic models, such as the Denavit-Hartenberg model, are not directly applicable to kinematic parameter identification. In this dissertation we introduce a new kinematic model, called the 5-Model, which is applicable to kinematic parameter identification, and use it as the foundation for our development of a general technique for identifying the kinematic parameters of any robot with rigid links.

Contenuti:

1. Introduction.- 1.1. Overview.- 1.2. Motivation.- 1.3. Dissertation Goals and Contributions.- 1.4. Dissertation Outline.- 2. Review of Robot Kinematics, Identification, and Control.- 2.1. Overview.- 2.2. Coordinate Frame Kinematic Models.- 2.2.1. Denavit-Hartenberg Model.- 2.2.2. Whitney-Lozinski Model.- 2.3. Models of Revolute Joint Manipulators.- 2.4. Modeling Assumptions.- 2.5. Kinematic Identification.- 2.6. Kinematic Control.- 2.7. Conclusions.- 3. Formulation of the S-Model.- 3.1. Overview.- 3.2. S-Model.- 3.3. Computing S-Model Parameters.- 3.4.Conclusions.- 4. Kinematic Identification.- 4.1. Overview.- 4.2.Kinematic Features.- 4.3 S-Model Identification.- 4.3.1. Overview.- 4.3.1.1. Feature Identification.- 4.3.1.2. Link Coordinate Frame Specification.- 4.3.1.3. S-Model Parameter Computation.- 4.3.1.4. Denavit-Hartenberg Parameter Extraction.- 4.3.2. Feature Identification.- 4.3.2.1. Plane-of-Rotation Estimation.- 4.3.2.2. Center-of-Rotation Estimation.- 4.3.2.3. Line-of-Translation Estimation.- 4.3.3. Link Coordinate Frame Specification.- 4.3.4. S-Model Parameters.- 4.3.5. Denavit-Hartenberg Parameters.- 4.4. Conclusions.- 5. Inverse Kinematics.- 5.1. Overview.- 5.2. Newton-Raphson Algorithm.- 5.3. Jacobi Iterative Method.- 5.4. Performance Evaluation.- 5.5. Comparative Computational Complexity.- 5.6. Conclusions.- 6. Prototype System and Performance Evaluation.- 6.1. Overview.- 6.2. System Overview.- 6.3. Sensor System.- 6.3.1. Description.- 6.4. Generating Features.- 6.5. Measuring Performance.- 6.5.1. One-Dimensional Grid.- 6.5.2. Two-Dimensional Grid.- 6.5.3. Three-Dimensional Grid.- 6.6. Kinematic Performance Evaluation.- 6.6.1. One-Dimensional Performance Evaluation.- 6.6.2. Two-Dimensional Performance Evaluation.- 6.6.3. Three-Dimensional Performance Evaluation.- 6.7. Conclusions.- 7. Performance Evaluation Based Upon Simulation.- 7.1. Overview.- 7.2. A Monte-Carlo Simulator.- 7.2.1. Evaluating Kinematic Performance.- 7.2.2. Design Model Control.- 7.2.3. Signature-Based Control.- 7.3. Simulator Verification.- 7.4. Results.- 7.4.1. Encoder Calibration Errors.- 7.4.2. Machining and Assembly Errors.- 7.4.3. Sensor Measurement Errors.- 7.4.4. Number of Measurements.- 7.4.5. Effect of Target Radius.- 7.5. Conclusions.- 8. Summary and Conclusions.- 8.1. Introduction.- 8.2. Summary and Contributions.- 8.3. Suggestions for Future Research.- Appendix A. Primitive Transformations.- Appendix B. Ideal Kinematics of the Puma 560.- B.1. Forward Kinematics.- B.2. Inverse Kinematics.- Appendix C. Inverse Kinematics.- C.1. Newton-Raphson Computations.- C.2. Jacobi Iterative Computations.- Appendix D. Identified Arm Signtaures.- Appendix E. Sensor Calibration.- E.1. Calibration Rods.- E.2. Slant Range Compensation.- Appendix F. Simulator Components.- F.1. Robot Manufacturing Error Model.- F.2. Simulator Input Parameters.- Appendix G. Simulation Results.- G.1. Encoder Calibration Errors.- G.2. Machining and Assembly Errors.- G.3. Sensor Measurement Errors.- G.4. Number of Measurements.- G.5. Target Radius.- References.