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C. Presse

dblp:98/4091 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1992
—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% Probabilistic and Bayesian machine learning · 33%

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

TopicWeightPapersLastEvidence papers
Machine learning › Probabilistic and Bayesian machine learning › statistical inference
bayesian inference		 0.011992
Bayesian estimation of inertial parameters of robots · ICRA 1992
Robotics › Motion planning and robot control › system identification › robot dynamics identification
inertial parameter identification		 0.011992
Bayesian estimation of inertial parameters of robots · ICRA 1992
Robotics › Motion planning and robot control › system identification
robot identification		 0.011992
Bayesian estimation of inertial parameters of robots · ICRA 1992

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

energy model · 0.0bayesian estimation · 0.0
YearPublicationVenuePosition
1992 Bayesian estimation of inertial parameters of robots
abstract
The authors present a Bayesian approach using an energy model to identify the base (identifiable) inertial parameters of a robot, given a prior statistical information (expected value and covariance matrix) about the solution vector. An application of a three-degree-of-freedom robot is simulated to show the efficiency of the method.>
C. Presse, Maxime Gautier
 ICRA1