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Federico Guidi

dblp:03/1311 · 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 · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › nonholonomic systems
nonholonomic vehicle control
0.012000
Vision-Based Dynamic Estimation and Set-Point Stabilization of Nonholonomic Vehicles · ICRA 2000
Robotics › Motion planning and robot control
robot control
0.012000
Vision-Based Dynamic Estimation and Set-Point Stabilization of Nonholonomic Vehicles · ICRA 2000
Robotics › Motion planning and robot control › robot control › sensor-based control
vision-based stabilization
0.012000
Vision-Based Dynamic Estimation and Set-Point Stabilization of Nonholonomic Vehicles · ICRA 2000
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.012000
Vision-Based Dynamic Estimation and Set-Point Stabilization of Nonholonomic Vehicles · ICRA 2000

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

optical flow · 0.0lyapunov-based design · 0.0
YearPublicationVenuePosition
2000 Vision-Based Dynamic Estimation and Set-Point Stabilization of Nonholonomic Vehicles
abstract
A nonhonolomic vehicle is stabilized to a desired pose through a visual servoing technique. The vision-based regulation of the nonholonomic vehicle proposed is built through a discontinuous change of coordinates and Lyapunov-based design, which ensure asymptotic stability of the closed-loop visual system. A dynamic estimation procedure, based on the optical flow equations, is also presented to deal with uncertainties in the obsereved environment. Simulations results on an autonomous mobile robot are reported, that show the practicality of the proposed approach.
Fabio Conticelli, Domenico Prattichizzo, Federico Guidi, Antonio Bicchi
ICRA3