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Johann Galie

dblp:35/1537 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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 · 62% Robot navigation and mapping · 38%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › underactuated robotics
overhead crane control
0.012000
Observing the Load Dynamic of an Overhead Crane with Minimal Sensor Equipment · ICRA 2000
Robotics › Robot navigation and mapping › state estimation
observability analysis
0.012000
Observing the Load Dynamic of an Overhead Crane with Minimal Sensor Equipment · ICRA 2000
Robotics › Robot navigation and mapping
state estimation
0.012000
Observing the Load Dynamic of an Overhead Crane with Minimal Sensor Equipment · ICRA 2000
YearPublicationVenuePosition
2000 Observing the Load Dynamic of an Overhead Crane with Minimal Sensor Equipment
abstract
Sensing the load dynamic in an overhead crane is not a simple task because both load angular position and velocity measurements are not easily attainable and subject to disturbances. A method to reconstruct the dynamic of the load is presented. It is based on the estimate of the torque that the load produces on the drive that governs the translational dynamic of the trolley at which the load is hanging. It requires a minimal sensor equipment, namely measures of the electrical torque and angular velocity of the drive, as both swing angle and load speed are shown to be observable for the linearized model.
Claudio Altafini, Ruggero Frezza, Johann Galie
ICRA3