Identification of the minimum inertial parameters of robots

Author(s):  
M. Gautier ◽  
W. Khalil
Keyword(s):  
Author(s):  
Saeed Ebrahimi ◽  
Jo´zsef Ko¨vecses

In this paper, we introduce a novel concept for parametric studies in multibody dynamics. This is based on a technique that makes it possible to perform a natural normalization of the dynamics in terms of inertial parameters. This normalization technique rises out from the underlying physical structure of the system, which is mathematically expressed in the form of eigenvalue problems. It leads to the introduction of the concept of dimensionless inertial parameters. This, in turn, makes the decomposition of the array of parameters possible for studying design and control problems where parameter estimation and sensitivity is of importance.


2013 ◽  
Vol 437 ◽  
pp. 663-668
Author(s):  
Ling Sun ◽  
Peng Yu ◽  
Tong Zhang

Inertial parameters of the motor assembly include its mass, CM (center of mass) position, moment of inertia and product of inertia. Taking one vehicle drive motor as the research object, its mass and CM position are measured by using weight method and moment balance method respectively. Its moment of inertia and product of inertia are measured by using three-wire pendulum. On the basis of analyzing the test error, this paper proposed specific measures to reduce the test error.


Author(s):  
Roberto Lampariello ◽  
Gerhard Hirzinger

A method is proposed for the identification of the inertial parameters of a free-flying robot directly in orbit, using accelerometers. This can serve to improve the path planning and tracking capabilities of the robot, as well as its efficiency in energy consumption. The method is applied to the identification of the base body and of the load on the end-effector, giving emphasis to the experimental design. The problem of the identification of the full system is also addressed in its theoretical aspects. The experience from the Getex Dynamic Motion experiments performed on the ETS-VII satellite have allowed to determine a most suitable model for the identification.


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