Advertisement

# Euler-Angle-Joints (EAJs)

• 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 frequently noted in the literature on robotics (Sugihara et al. 2002; Kurazume et al. 2003; Vukobratovic et al. 2007; Kwon and Park 2009) and mechanisms (Duffy 1978; Chaudhary and Saha 2007), a higher Degrees-of-Freedom (DOF) joint, say, a universal, a cylindrical or a spherical joint, can be represented using a combination of several intersecting 1-DOF joints. For example, a universal joint also known as Hooke’s joint is a combination of two revolute joints, the axes of which intersect at a point, whereas a cylindrical joint is a combination of a revolute joint and a prismatic joint. Similarly, the kinematic behavior of a spherical joint may be simulated by the combination of three revolute joints whose axes intersect at a point. The joint axes can be represented using the popular Denavit and Hartenberg (DH) parameters (Denavit and Hartenberg 1955). For the spherical joints, an alternative approach using the Euler angles can also be adopted, as there are three variables. For spatial rotations, one may also use other minimal set representations like Bryant (or Cardan) angles, Rodriguez parameters, etc. or non-minimal set representation like Euler parameters, quaternion, etc. The non-minimal sets are not considered here due the fact that the dynamic models obtained in this book are desired in minimal sets. The minimal sets, other than Euler/Bryant angles, are discarded here as they do not have direct correlation with the axis-wise rotations. It is worth mentioning that the fundamental difference between the Euler and Bryant angles lies in a fact that the former represents a sequence of rotations about the same axis separated with a rotation about a different axis, denoted as α–β–α, whereas the latter represents the sequence of rotations about three different axes, denoted as α–β–γ. They are also commonly referred to as symmetric and asymmetric sets of Euler angles in the literature. For convenience, the name Euler angles will be referred to both Euler and Bryant angles, hereafter.

## Keywords

Joint Angle Rotation Matrix Euler Angle Twist Angle Revolute Joint
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. Chaudhary, H., & Saha, S. K. (2007). Constraint wrench formulation for closed-loop systems using Two-level recursions. ASME Journal of Mechanical Design, 129, 1234–1242.
2. Craig, J. J. (2006). Introduction to robotics, mechanics and control. Delhi: Pearson Education.Google Scholar
3. Denavit, J., & Hartenberg, R. S. (1955). A kinematic notation for lower-pair mechanisms based on matrices. Journal of Applied Mechanics, 22, 215–221.
4. Duffy, J. (1978). Displacement analysis of the generalized RSSR mechanism. Mechanism and Machine Theory, 13, 533–541.
5. Khalil, W., & Kleinfinger, J. (1986). A new geometric notation for open and closed-loop robots. IEEE International Conference on Robotics and Automation, 3, 1174–1179.Google Scholar
6. Kurazume, R., Hasegawa, T., & Yoneda, K. (2003). The sway compensation trajectory for a biped robot. IEEE International Conference on Robotics and Automation, 1, 925–931.Google Scholar
7. Kwon, O., & Park, J. H. (2009). Asymmetric trajectory generation and impedance control for running of biped robots. Autonomous Robots, 26(1), 47–78.
8. Shabana, A. A. (2001). Computational dynamics. New York: Wiley.
9. Shah, S. V., Saha, S. K., & Dutt, J. K. (2012b). Denavit-Hartenberg (DH) Parametrization of Euler Angles. ASME J of Nonlinear and Computational Dynamics, 7(2).Google Scholar
10. Shuster, M. D., & Oh, S. D. (1981). Three-axis attitude determination from vector observation. Journal of Guidance, Control and Dynamics, 4(1), 70–77.
11. Singla, P., Mortari, D., & Junkins, J. L. (2004). How to avoid singularity for Euler Angle Set?. AAS space flight mechanics conference, Hawaii.Google Scholar
12. Sugihara, T., Nakamura, Y., & Inoue, H. (2002). Realtime Humanoid motion generation through ZMP manipulation based on inverted pendulum control. IEEE International Conference on Robotics and Automation, 2, 1404–1409.Google Scholar
13. Vukobratovic, M., Potkonjak, V., Babkovic, K., & Borovac, B. (2007). Simulation model of general human and humanoid motion. Multibody System Dynamics, 17(1), 71–96.
14. Wittenburg, J. (2008). Dynamics of multibody systems. Berlin: Sprnger.

## 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