Kinematic Calibration of Robotic Mechanism

Author(s):  
Tao Sun ◽  
Shuofei Yang ◽  
Binbin Lian
ROBOT ◽  
2013 ◽  
Vol 35 (5) ◽  
pp. 600 ◽  
Author(s):  
Wenbin GAO ◽  
Hongguang WANG ◽  
Yong JIANG ◽  
Xin'an PAN

2009 ◽  
Vol 1 (3) ◽  
Author(s):  
Chunshi Feng ◽  
Shuang Cong ◽  
Weiwei Shang

In this paper, the kinematic calibration of a planar two-degree-of-freedom redundantly actuated parallel manipulator is studied without any assumption on parameters. A cost function based on closed-loop constraint equations is first formulated. Using plane geometry theory, we analyze the pose transformations that bring infinite solutions and present a kinematic calibration integrated of closed-loop and open-loop methods. In the integrated method, the closed-loop calibration solves all the solutions that fit the constraint equations, and the open-loop calibration guarantees the uniqueness of the solution. In the experiments, differential evolution is applied to compute the solution set, for its advantages in computing multi-optima. Experimental results show that all the parameters involved are calibrated with high accuracy.


CIRP Annals ◽  
2006 ◽  
Vol 55 (1) ◽  
pp. 1-6 ◽  
Author(s):  
A. Watanabe ◽  
S. Sakakibara ◽  
K. Ban ◽  
M. Yamada ◽  
G. Shen ◽  
...  

Author(s):  
Nicolas Andreff ◽  
Pierre Renaud ◽  
Philippe Martinet ◽  
Franc¸ois Pierrot

2014 ◽  
Vol 21 (1) ◽  
pp. 85-98 ◽  
Author(s):  
Jorge Santolaria ◽  
Javier Conte ◽  
Marcos Pueo ◽  
Carlos Javierre

Abstract Screw axis measurement methods obtain a precise identification of the physical reality of the industrial robots’ geometry. However, these methods are in a clear disadvantage compared to mathematical optimisation processes for kinematical parameters. That’s because mathematical processes obtain kinematical parameters which best reduce the robot errors, despite not necessarily representing the real geometry of the robot. This paper takes the next step at the identification of a robot’s movement from the identification of its real kinematical parameters for the later study of every articulation’s rotation. We then obtain a combination of real kinematic and dynamic parameters which describe the robot’s movement, improving its precision with a physical understanding of the errors.


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