- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Table of Contents
Advances in Mechanical Engineering
Volume 2013 (2013), Article ID 280453, 7 pages
Research on Flexible Joint Stiffness Test and Trajectory Planning of Space Manipulator
1Department of Mechanics, School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
2Automotive and Transportation Engineering Institute, Guangxi University of Science and Technology, Liuzhou 545006, China
3China Academy of Space Technology, Beijing 100094, China
Received 23 August 2013; Revised 15 October 2013; Accepted 23 October 2013
Academic Editor: Xiaoting Rui
Copyright © 2013 Yongtai Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Both Natural Coordinate Formulation describing rigid bodies and Absolute Nodal Coordinate Formulation describing flexible bodies are used to model a flexible manipulator with flexible joint and flexible link. The torsional stiffness of flexible joint is tested using a specialized stiffness test equipment, and then the nonlinear torsional stiffness is determined by fitting the experimental data. A new trajectory planning function called the cosine-based function is proposed to design the joint trajectory, which is smoother than the fifth-polynomial and cycloidal motion functions. Finally, a one-link manipulator with flexible joint and flexible link is used to compare the performance of the three trajectory planning functions. Results show that residual vibration can be remarkably reduced by the proposed cosine-based function, which exhibits a significantly better performance than the fifth-polynomial and cycloidal motion functions.
A space manipulator undertakes tasks of cabin translocation, transfer, and installation of equipment, as well as serves as an astronaut auxiliary in a station system. It serves an important function in space engineering, with the advantages of lighter structure, lower launching cost, higher operational speed, greater payload-to-manipulator-weight ratio, smaller actuators, lower energy consumption, and better maneuverability. However, the greatest disadvantage of the space manipulator is the vibration problem due to the flexibility of the joint and link. For instance, it took many cumulative hours in order to damp down the residual vibration in the remote manipulator system in a Space Station-assembly Shuttle flight, which occupied 20% to 30% of the total time . The residual vibration significantly reduces the end-point accuracy of the manipulator. Therefore, the best scheme is in which the flexible manipulator completes the required move with minimal residual vibration.
Joint flexibility and link flexibility are basic reasons of manipulator vibration, which cannot be neglected in the dynamic modeling. Spong  first modeled the flexible joint as a linear spring, and this modeling technique was adopted by most researchers [3, 4]. However, simple linear spring is not capable of describing the flexible joint precisely. In the dynamic modeling of flexible link, the assumed mode method is typically used by most researchers. Martins et al.  and Tso et al.  studied a flexible manipulator using the Lagrangian equation and the assumed mode method. In assumed mode model formulation, the link flexibility is usually represented by a truncated finite modal series in terms of spatial mode eigenfunctions and time-varying mode amplitudes. The main drawback of this method is that there are several ways to choose link boundary conditions and mode eigenfunctions. Moreover, the assumed mode method is only capable of describing small deformation, not large deformation. The previous works solely focused on either joint flexibility or link flexibility.
Several different approaches have been suggested to reduce residual vibration, which can be categorized as active control, passive control, and trajectory planning methods. Different trajectories of joint space, significantly affect the vibration of a flexible manipulator. The fifth-polynomial function is widely used to plan the joint trajectory, but it contains the undesirable higher harmonics that excite the system resonances. Cycloidal motion  is another trajectory planning function of joint space, whose performance is not clear.
Due to the above deficiencies in the previous work, both Natural Coordinate Formulation (NCF)  describing rigid bodies and Absolute Nodal Coordinate Formulation (ANCF) [9, 10] especially suitable for flexible bodies with large deformation are applied to model the flexible manipulator in this paper. The flexibilities of joint and link are simultaneously considered in the dynamic model. The torsional stiffness of flexible joint is tested by a specialized stiffness test equipment, and the nonlinear torsional stiffness is finally determined by fitting the experiment data, which is more precise than the constant torsional stiffness in describing the flexible joint. To suppress the residual vibration, a new planning function called the cosine-based function is proposed to design the joint trajectory. Finally, a one-link manipulator with flexible joint and flexible link is used to verify the effectiveness of the proposed cosine-based function.
This paper is organized as follows. Section 2 is dedicated to the dynamic modeling of a flexible manipulator by NCF and ANCF, with flexible joint and flexible link considered. Section 3 is devoted to the torsional stiffness test for the flexible joint. In Section 4, two trajectory planning functions of the joint are introduced first and then a new planning function called the cosine-based function is proposed. Section 5 gives simulation results and analyses. Finally, the related conclusions are drawn in Section 6.
2. Dynamic Modeling of a Flexible Manipulator
The one-link manipulator with flexible joint and flexible link is shown in Figure 1. The motor rotor and the joint shell are rigid bodies modeled by NCF. They are connected by a torsional spring, whose stiffness is determined from the test experiment introduced in Section 3. The link is a flexible body modeled by ANCF.
NCF is adopted to describe rigid bodies, as shown in Figure 2. The position vectors of two fixed points and two unit vectors on the rigid body are set as generalized coordinates expressed as
The global position vector of an arbitrary point on the rigid body can be written as where is the element shape function expressed as where is the unit matrix and , , and are constant components of the local coordinate.
According to the principle of virtual work, the constant mass matrix can be determined as
The three-dimensional beam element of two nodes described by ANCF, as shown in Figure 3, as first proposed by Shabana and Yakoub [9, 10], is used to describe the flexible link. The generalized coordinates of the beam element are written as
The global position vector of an arbitrary point on the body can be written as where is the element shape function expressed as where is the unit matrix. , , , , , , , ; , , and . , , and are the local coordinates of the element. , and is the initial length of the element.
By using the first class of Lagrange’s equation, the equations of the motions for constrained rigid-flexible multibody systems can be expressed in a compact form as a set of differential and algebraic equations written as  where is the mass matrix, denotes the generalized coordinates, stands for the constraint equations, is the Jacobi of constraint equations, is the Lagrangian multiplier, is the generalized external force, and is the generalized elastic force. The calculation of the elastic force and its Jacobi can be referred to in [12, 13].
Several algorithms can be used to solve differential-algebraic equations of multibody system numerically. These algorithms include the Baumgarte, Newmark, generalized-a, and augmented Lagrangian methods. In this paper, the iteration strategy of the generalized-a method proposed by Arnold and Brls  and the scaling technology proposed by Bottasso et al.  are adopted for numerically solving the differential-algebraic equations efficiently and precisely.
3. Torsional Stiffness Test for the Flexible Joint
The specialized stiffness test equipment developed by our research group is used to test the torsional stiffness of the flexible joint. The optical schematic of double angle is shown in Figure 4. The laser beam emitted by the laser locates at point on the screen after being reflected by the mirror. According to the basic optical principle, if the mirror rotates by degree, the reflected laser beam rotates by 2 degree, and the laser spot on the screen moves from point to point . Let the moving distance of the laser spot be , and let the distance from the mirror to the screen be . is generally significantly greater than ; that is, . Thus, has a small value. According to the triangle geometry, the rotation angle of the mirror can be obtained as
The stiffness test schematic is shown in Figure 5. Let be the measuring point and let be the reference point. Two mirrors are attached to points and separately. The two lasers emit laser beams, and the laser beams, respectively, locate at points and on the screen after being reflected by the mirrors. When torque is applied to the joint, the two mirrors rotate by and . According to the basic optical principle, the reflected laser beams rotate by and , and the laser spots on the screen move from points and to points and , respectively. The moving distances of laser spots are and . Then, the rotational angle of the measuring point relative to the rotational angle of the datum point can be obtained as
A mechanical testing machine is used to apply torque to the joint, after which the relative angle is measured. The typical - curve is shown in Figure 6.
The torque-angle curve has two segments: nonlinear and linear. The quadratic polynomial is adopted to fit the nonlinear segment, whereas the least square method is adopted to fit the linear segment. Finally, the relationship between torque and angle can be expressed by the following formula: where is the turning point between nonlinear segment and linear segment and is the stiffness of linear segment.
The nonlinear stiffness of the joint, as shown in Figure 7, can be obtained by differentiating the above equation.
4. Trajectory Planning of the Joint
In engineering, smooth and continuous functions are typically adopted to plan the joint trajectory, the first and second derivatives of which are also smooth and continuous, such as the fifth-polynomial and cycloidal motion functions. The six boundary conditions of angle, angular velocity, and angular acceleration of the joint are as follows: where is the planning time, is the initial angle of joint, and is the final angle of joint.
The fifth-polynomial is adopted to plan the joint trajectory. The polynomial coefficients are obtained by the six boundary conditions described by (12). Finally, the angle, angular velocity, and angular acceleration of the joint are as follows:
Cycloidal motion is adopted to plan the joint trajectory expressed as
The angular velocity and angular acceleration of the joint can be obtained by differentiating the above equation and can be determined as
Cycloidal motion can evidently satisfy all boundary conditions described by (12).
In this paper, a cosine-based function is proposed to plan the joint trajectory, and it can be written as
According to the six boundary conditions described by (12), the three unknown coefficients , , and can be determined. Finally, the angle, angular velocity, and angular acceleration of the joint are as follows:
The maximal angular velocity and angular acceleration of the fifth-polynomial, cycloidal motion, and cosine-based functions are shown in Table 1. The ratio of the maximal angular velocity of the three functions is 1 : 1.07 : 1.26, and the ratio of the maximal angular acceleration of the three functions is 1 : 1.09 : 1.48.
The planning time is set to be 1 [s], the initial angle is set to be , and the final angle is set to be .
Figures 8, 9, and 10 show the angle, angular velocity, and angular acceleration of the three planning functions, respectively. The angle, angular velocity, and angular acceleration of the cosine-based function are smoother than those of the fifth-polynomial and cycloidal motion functions at the initial and final times, whereas the maximal angular velocity and the maximal angular acceleration of the cosine-based function are larger than those of the fifth-polynomial and cycloidal motion functions.
5. Simulation Studies
The planning time is set to be 1 [s], the simulation time is set to be 2 [s], the initial angle of the joint is set to be , and the final angle of the joint is set to be .
The geometrical parameters and mechanical parameters of the flexible link are shown in Table 2. Also, six ANCF three-dimensional beam elements are used to discretized the flexible link.
The above three planning functions are used to plan the joint trajectory. The motor is driven by the speed mode; that is, the motor rotor is assumed to be capable of absolutely tracking the given trajectory using the three planning functions, respectively. To determine the effects of the three planning functions on manipulator vibration, two cases are studied: with joint flexibility considered and with joint flexibility and link flexibility considered.
Figure 11 shows the angle errors of the three planning functions with joint flexibility considered. In the course of motion (), the maximal angle errors of the fifth-polynomial, cycloidal motion, and cosine-based functions are, respectively, 0.056°, 0.052°, and 0.056°, whereas after motion (), the residual angle errors are, respectively, 0.028°, 0.019°, and 0.002°. The tracking errors caused by the three functions are evidently similar in the course of motion, but the residual vibration caused by the proposed cosine-based function is far less than that caused by the fifth-polynomial and cycloidal motion functions after motion.
Figure 12 shows the angle errors of the joint of the three planning functions with joint flexibility and link flexibility considered. Figure 13 shows the vibration of the endpoint of the three planning functions with joint flexibility and link flexibility considered. In the course of motion (), the maximal angle errors of the fifth-polynomial, cycloidal motion, and cosine-based functions are, respectively, 0.069°, 0.070°, and 0.095°, whereas the maximal vibration amplitudes of the endpoint are, respectively, 1.84 cm, 1.87 cm, and 2.38 cm. After motion (), the maximal residual angle errors are, respectively, 0.060°, 0.040°, and 0.012°, whereas the maximal residual vibration amplitudes of the endpoint are, respectively, 1.43 cm, 1.03 cm, and 0.10 cm. The tracking errors caused by the three functions are evidently similar in the course of motion, but the error caused by the cosine-based function is a lightly higher. However, the residual vibration caused by the cosine-based function is significantly less than that caused by the fifth-polynomial and cycloidal motion functions after motion.
The above analysis shows that, whether with joint flexibility considered or with both joint flexibility and link flexibility considered, the tracking errors caused by the three planning functions are similar in the course of motion, but the residual vibration caused by the cosine-based function proposed in this paper is significantly less than that caused by the fifth-polynomial and cycloidal motion functions after motion. We can thus conclude that the cosine-based planning function proposed in this paper is more effective in weakening the residual vibration than the fifth-polynomial planning and cycloidal motion planning functions.
The flexible manipulator is modeled by NCF and ANCF, considering the flexibility of joint and link. The nonlinear torsional stiffness is finally determined by fitting the experimental data. Moreover, a cosine-based function is proposed to suppress the residual vibration. The maximal angular velocity ratio and angular acceleration ratio of the fifth-polynomial, cycloidal motion, and cosine-based functions are, respectively, 1 : 1.07 : 1.26 and 1 : 1.09 : 1.48. A one-link manipulator with flexible joint and flexible link is used to evaluate the proposed trajectory planning function. Results show that the residual vibration by the proposed cosine-based function is reduced to 7.1% of that by the fifth-polynomial function and to 9.7% of that by the cycloidal motion function.
Notably, the effectiveness of the proposed cosine-based function in weakening the residual vibration is only verified by numerical simulations. The corresponding experimental validation is left for our future work.
This work is supported by Grant 10972033 of the Natural Science Foundation of China. This work is also supported by Grant 20100141107 of the China Academy of Space Technology.
- S. Dubowsky, “Dealing with vibrations in the deployment structures of space robotic systems,” in Proceedings of the 5th International Conference on Adaptive Structures, pp. 5–7, Sendai International Center, Sendai, Japan, 1994.
- M. W. Spong, “Modeling and control of elastic joint robots,” Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, vol. 109, no. 1, pp. 310–319, 1987.
- S. K. Ider and M. K. Özgören, “Trajectory tracking control of flexible-joint robots,” Computers and Structures, vol. 76, no. 6, pp. 757–763, 2000.
- G. Magnani, P. Rocco, and A. Rusconi, “Modeling and position control of a joint prototype of DEXARM,” in Proceedings of the 10th International Workshop on Advanced Motion Control (AMC' 08), pp. 562–567, March 2008.
- J. Martins, M. Ayala Botto, and J. S. Da Costa, “Modeling of flexible beams for robotic manipulators,” Multibody System Dynamics, vol. 7, no. 1, pp. 79–100, 2002.
- S. K. Tso, T. W. Yang, W. L. Xu, and Z. Q. Sun, “Vibration control for a flexible-link robot arm with deflection feedback,” International Journal of Non-Linear Mechanics, vol. 38, no. 1, pp. 51–62, 2003.
- A. Abe, “Trajectory planning for residual vibration suppression of a two-link rigid-flexible manipulator considering large deformation,” Mechanism and Machine Theory, vol. 44, no. 9, pp. 1627–1639, 2009.
- D. J. García and E. Bayo, Kinematic and Dynamic Simulation of Multibody Systems: the Real-Time Challenge, Springer, New York, NY, USA, 1994.
- A. A. Shabana and R. Y. Yakoub, “Three dimensional absolute nodal coordinate formulation for beam elements: theory,” Journal of Mechanical Design, vol. 123, no. 4, pp. 606–613, 2001.
- R. Y. Yakoub and A. A. Shabana, “Three dimensional absolute nodal coordinate formulation for beam elements: implementation and applications,” Journal of Mechanical Design, vol. 123, no. 4, pp. 614–621, 2001.
- A. A. Shabana, Computational Dynamics, John Wiley & Sons, New York, NY, USA, 3rd edition, 2010.
- D. García-Vallejo, J. Mayo, J. L. Escalona, and J. Domínguez, “Efficient evaluation of the elastic forces and the jacobian in the absolute nodal coordinate formulation,” Nonlinear Dynamics, vol. 35, no. 4, pp. 313–329, 2004.
- C. Liu, Q. Tian, and H. Hu, “Efficient computational method for dynamics of flexible multibody systems based on absolute nodal coordinate,” Journal of Theoretical and Applied Mechanics, vol. 42, no. 6, pp. 1197–1205, 2010 (Chinese).
- M. Arnold and O. Brüls, “Convergence of the generalized-α scheme for constrained mechanical systems,” Multibody System Dynamics, vol. 18, no. 2, pp. 185–202, 2007.
- C. L. Bottasso, D. Dopico, and L. Trainelli, “On the optimal scaling of index three DAEs in multibody dynamics,” Multibody System Dynamics, vol. 19, no. 1-2, pp. 3–20, 2008.