PV-OSIMr: A Lowest Order Complexity Algorithm for Computing the Delassus Matrix

We present PV-OSIMr, an efficient algorithm for computing the Delassus matrix (also known as the inverse operational space inertia matrix) for a kinematic tree, with the lowest order computational complexity known in literature. PV-OSIMr is derived by optimizing the recently proposed PV-OSIM algorithm using the compositionality of the force and motion propagators. It has a computational complexity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n+m^{2})$</tex-math></inline-formula> compared to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ O(n + m^{2}d)$</tex-math></inline-formula> of the PV-OSIM algorithm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n+md +m^{2})$</tex-math></inline-formula> of the extended force propagator algorithm (EFPA), where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is the number of joints, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> is the number of constraints and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> is the depth of the kinematic tree. Since the Delassus matrix is an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m \times m$</tex-math></inline-formula> sized matrix and its computation must consider all the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> joints, PV-OSIMr's asymptotic computational complexity is optimal. We further benchmark our algorithm and find it to be often more efficient than the PV-OSIM and EFPA in practice.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-09-27
DOI
https://doi.org/10.1109/lra.2024.3469829
Citations
1
Primary Topic
Digital Filter Design and Implementation
Type
article
Field-Weighted Citation Impact
0.35

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article

PV-OSIMr: A Lowest Order Complexity Algorithm for Computing the Delassus Matrix

Ajay Suresha Sathya, Wilm Decré, Jan Swevers
1 citations
IEEE Robotics and Automation Letters
Digital Filter Design and Implementation
0.35
article

PV-OSIMr: A Lowest Order Complexity Algorithm for Computing the Delassus Matrix

Ajay Suresha Sathya, Wilm Decré, Jan Swevers
article en
1 citations

Abstract

We present PV-OSIMr, an efficient algorithm for computing the Delassus matrix (also known as the inverse operational space inertia matrix) for a kinematic tree, with the lowest order computational complexity known in literature. PV-OSIMr is derived by optimizing the recently proposed PV-OSIM algorithm using the compositionality of the force and motion propagators. It has a computational complexity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n+m^{2})$</tex-math></inline-formula> compared to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ O(n + m^{2}d)$</tex-math></inline-formula> of the PV-OSIM algorithm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(n+md +m^{2})$</tex-math></inline-formula> of the extended force propagator algorithm (EFPA), where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is the number of joints, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> is the number of constraints and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> is the depth of the kinematic tree. Since the Delassus matrix is an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m \times m$</tex-math></inline-formula> sized matrix and its computation must consider all the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> joints, PV-OSIMr's asymptotic computational complexity is optimal. We further benchmark our algorithm and find it to be often more efficient than the PV-OSIM and EFPA in practice.

IEEE Robotics and Automation LettersVol. 9(11)
Université Paris Sciences et Lettres (FR), Flanders Make (Belgium) (BE), Neuroelectronics Research Flanders (BE), Département d'Informatique (FR), KU Leuven (BE)
Flanders Make, Fonds Wetenschappelijk Onderzoek, Vlaamse regering
Openalex Percentile: Top 44%
Digital Filter Design and Implementation
0.35
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