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Article overview
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Observability in Inertial Parameter Identification | Patrick M. Wensing
; Günter Niemeyer
; Jean-Jacques E. Slotine
; | Date: |
10 Nov 2017 | Abstract: | We present an algorithm to characterize the space of identifiable inertial
parameters in system identification of an articulated robot. This problem has
been considered in the literature for decades; however, existing methods suffer
from common drawbacks. Methods either rely on symbolic techniques that do not
scale, or rely on numerical techniques that are sensitive to the choice of an
input motion. The contribution of this work is to propose a recursive algorithm
for this problem that requires only the structural parameters of a mechanism as
its input. This Recursive Parameter Nullspace Algorithm (RPNA) can be applied
to general open-chain kinematic trees, and does not rely on symbolic
techniques. Drawing on the exponential parameterization of rigid-body
kinematics, classical linear controllability and observability results can be
directly applied to inertial parameter identifiability. The high-level
operation of the RPNA is based on a key observation -- undetectable changes in
inertial parameters can be interpreted as sequences of inertial transfers
across the joints. This observation can be applied recursively, and lends an
overall complexity of O(N) to determine the minimal parameters for a system of
N bodies. Matlab source code for the new algorithm is provided. | Source: | arXiv, 1711.3896 | Services: | Forum | Review | PDF | Favorites |
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