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Benoit P. Cloutier

dblp:00/1161 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 67% Robot manipulation · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot dynamics
forward dynamics
0.011995
The Formulation Stiffness of Forward Dynamics Algorithms and Implications for Robot Simulation · ICRA 1995
Robotics › Motion planning and robot control › robot dynamics
multibody dynamics
0.011995
The Formulation Stiffness of Forward Dynamics Algorithms and Implications for Robot Simulation · ICRA 1995
Robotics › Robot manipulation
robot simulation
0.011995
The Formulation Stiffness of Forward Dynamics Algorithms and Implications for Robot Simulation · ICRA 1995

Methods — techniques the papers use, named apart from their topics

composite rigid body method · 0.0articulated-body method · 0.0adaptive stepsize integration · 0.0
YearPublicationVenuePosition
1995 The Formulation Stiffness of Forward Dynamics Algorithms and Implications for Robot Simulation
abstract
The authors identify an important phenomenon they call "formulation stiffness" in the numerical simulation of tree-structured multibody systems such as robot manipulators. The numerical simulation problem is usually treated as two separate problems: (i) the forward dynamics problem for computing system accelerations, and (ii) the numerical integration problem far advancing the state in time. The authors show that the interaction of these two problems leads to new conclusions about the overall efficiency of multibody simulation algorithms; in particular the fastest forward dynamics methods are not necessarily best when considered in conjunction with the popular adaptive stepsize integration methods. Specifically, the authors show that the articulated-body method is better suited to deal with certain types of numerical problems than the composite rigid body method. The authors present examples of simulations and discuss the practical implications of these results.
Benoit P. Cloutier, Dinesh K. Pai, Uri M. Ascher
ICRA1