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Nicholas A. Lynch

dblp:53/6747 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2007
—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 · 72% Robot manipulation · 28%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › micromanipulation
microassembly
0.112007
A Strategy for Vision-Based Controlled Pushing of Microparticles · ICRA 2007
Robotics › Motion planning and robot control › robot control › sensor-based control
vision-based control
0.112007
A Strategy for Vision-Based Controlled Pushing of Microparticles · ICRA 2007
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.112007
A Strategy for Vision-Based Controlled Pushing of Microparticles · ICRA 2007
Robotics › Motion planning and robot control › motion planning › geometric motion planning
cell decomposition
0.012007
A Strategy for Vision-Based Controlled Pushing of Microparticles · ICRA 2007
Robotics › Motion planning and robot control
path planning
0.012007
A Strategy for Vision-Based Controlled Pushing of Microparticles · ICRA 2007

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

wavefront expansion · 0.1nonholonomic modeling · 0.1atomic force microscope probe · 0.1
YearPublicationVenuePosition
2007 A Strategy for Vision-Based Controlled Pushing of Microparticles
abstract
In this paper, a strategy for controlled pushing is presented for microassembly of 4.5 mum polystyrene particles on a flat glass substrate using an atomic force microscope probe tip. Real-time vision based feedback from a CCD camera mounted to a high resolution optical microscope is used to track particle positions relative to the tip and target position. Tip-particle system is modeled in 2D as a nonholonomic differential drive robot. Effectiveness of the controller is demonstrated through experiments performed using a single goal position as well as linking a series of target positions to form a single complex trajectory. Cell decomposition and wavefront expansion algorithms are implemented to autonomously locate a navigable path to a specified target position. Control strategy alleviates problem of slipping and spinning during pushing.
Nicholas A. Lynch, Cagdas D. Onal, Eugenio Schuster, Metin Sitti
ICRA1