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Timothy Tuttle

dblp:82/6480 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1996
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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
Robot manipulation · 56% Motion planning and robot control · 44%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › actuator design
harmonic drive
0.011996
A nonlinear model of a harmonic drive gear transmission · IEEE Trans. Robotics Autom. 1996
Robotics › Motion planning and robot control › dynamic modeling
nonlinear dynamic modeling
0.011996
A nonlinear model of a harmonic drive gear transmission · IEEE Trans. Robotics Autom. 1996
Robotics › Robot manipulation › robot design
robot joint design
0.011996
A nonlinear model of a harmonic drive gear transmission · IEEE Trans. Robotics Autom. 1996

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

experimental system identification · 0.0dynamic modeling · 0.0
YearPublicationVenuePosition
1996 A nonlinear model of a harmonic drive gear transmission
abstract
Harmonic drives can exhibit very nonlinear dynamic behavior. In order to capture this behavior, not only must dynamic models include accurate representations of transmission friction, compliance, and kinematic error, but also important features of harmonic-drive gear-tooth geometry and interaction must be understood. In this investigation, experimental observations were used to guide the development of a model to describe harmonic-drive operation. Unlike less detailed representations, this model was able to replicate many of the features observed in actual harmonic-drive dynamic response. Unfortunately, since model parameters can only be derived from careful analysis of experimental dynamic response, it seems unlikely that any comparably sufficient representation can be constructed with parameter values obtained from catalogs or simple experimental observations.
Timothy Tuttle, Warren P. Seering
IEEE Trans. Robotics Autom.1