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Dynamics of Tree-Type Robotic Systems

  • Suril Vijaykumar Shah
  • Subir Kumar Saha
  • Jayanta Kumar Dutt
Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 62)

Abstract

As reviewed in Chap. 2, Newton-Euler (NE) equations of motion are found to be popular in dynamic formulations. Several methods were also proposed by various researchers to obtain the Euler-Langrage’s form of NE equations of motion. One of these methods is based on velocity transformation of the kinematic constraints, e.g., the Natural Orthogonal Complement (NOC) or the Decoupled NOC (DeNOC), as obtained in Chap. 4. The DeNOC matrices of Eq. (4.28) are used in this chapter to obtain the minimal order dynamic equations of motion that have several benefits.

Keywords

Mass Matrix Block Element Analytical Inversion Velocity Transformation Kinematic Module 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Angeles, J., & Ma, O. (1988). Dynamic simulation of N-axis serial robotic manipulators using a natural orthogonal complement. International Journal of Robotics Research, 7(5), 32–47.CrossRefGoogle Scholar
  2. Featherstone, R. (1983). The calculation of robotic dynamics using articulated body inertias. International Journal of Robotics Research, 2, 13–30.CrossRefGoogle Scholar
  3. Featherstone, R. (2005). Efficient factorization of the joint-space inertia matrix for branched kinematic tree. International Journal of Robotics Research, 24(6), 487–500.CrossRefGoogle Scholar
  4. Greenwood, D. T. (1988). Principles of dynamics. New Delhi: Prentice-Hall.Google Scholar
  5. Lilly, K. W., & Orin, D. E. (1991). Alternate formulations for the manipulator inertia matrix. International Journal of Robotics Research, 10(1), 64–74.CrossRefGoogle Scholar
  6. Rodriguez, G., Jain, A., & Kreutz-Delgado, K. (1991). A spatial operator algebra for manipulator modeling and control. International Journal of Robotics Research, 10(4), 371–381.CrossRefGoogle Scholar
  7. Saha, S. K. (1997). A decomposition of the manipulator inertia matrix. IEEE Transactions on Robotics and Automation, 13(2), 301–304.CrossRefGoogle Scholar
  8. Saha, S. K. (1999a). Analytical expression for the inverted inertia matrix of serial robots. International Journal of Robotic Research, 18(1), 116–124.Google Scholar
  9. Saha, S. K. (1999b). Dynamics of serial multibody systems using the decoupled natural orthogonal complement matrices. ASME Journal of Applied Mechanics, 66, 986–996.CrossRefGoogle Scholar
  10. Saha, S. K., & Schiehlen, W. O. (2001). Recursive kinematics and dynamics for closed loop multibody systems. International Journal of Mechanics of Structures and Machines, 29(2), 143–175.CrossRefGoogle Scholar
  11. Shah, S. V., Saha, S. K., & Dutt, J. K. (2012a). Modular framework for dynamics of tree-type legged robots. Mechanism and Machine Theory, Elsevier, 49, 234–255.CrossRefGoogle Scholar
  12. Stelzle, W., Kecskeméthy, A., & Hiller, M. (1995). A comparative study of recursive methods. Archive of Applied Mechanics, 66, 9–19.zbMATHGoogle Scholar
  13. Stewart, G. W. (1973). Introduction to matrix computations. Orlando: Academy Press.zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Suril Vijaykumar Shah
    • 1
  • Subir Kumar Saha
    • 2
  • Jayanta Kumar Dutt
    • 2
  1. 1.McGill UniversityMontrealCanada
  2. 2.Department of Mechanical EngineeringIIT DelhiNew DelhiIndia

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