Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Rares Stanciu 0002

dblp:204/9159-2 · also Rares I. Stanciu 0002 · DBLP profile ↗
← Back
3ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 3 · 2 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 · 100%
Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.012004
Feedforward Control for Human-in-the-loop Camera Systems · ICRA 2004
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.012004
Feedforward Control for Human-in-the-loop Camera Systems · ICRA 2004
Human-robot interaction
human-in-the-loop control
0.012004
Feedforward Control for Human-in-the-loop Camera Systems · ICRA 2004

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

feedforward control · 0.1alpha-beta-gamma filter · 0.1
YearPublicationVenuePosition
2006 Visual Servoing to Help Camera Operators Track Better
abstract
Platforms like gantries, booms, aircraft and submersibles are equipped with cameras. People teleoperate such platforms to capture desired views of a scene or a target. To avoid collisions with the environment and occluded views, such platforms are often equipped with redundant degrees-of-freedom. The operator must manually coordinate multiple degrees-of-freedom in order to get desired views. Tracking moving targets becomes especially tedious and often requires several highly skilled operators. Visual servoing some degrees-of-freedom may reduce operator burden and improve tracking performance. This video showcases the results using such an approach.
Paul Y. Oh, Rares Stanciu 0002
IROS2
2004 Feedforward Control for Human-in-the-loop Camera Systems
abstract
Cameras are often mounted on platforms that can move like rovers, booms, gantries and aircraft. People operate such platforms to capture desired views of a scene or a target. To avoid collisions with the environment and occlusions, such platforms often possess redundant degrees-of-freedom. As a result, manual manipulating of such platforms demands much skill. Visual-servoing some degrees-of-freedom may reduce operator burden and improve tracking performance. This concept, which we call human-in-the-loop visual-servoing, is demonstrated And applies a /spl alpha/ /spl rarr/ /spl beta/ /spl rarr/ /spl gamma/ filter and feedforward controller to a broadcast camera boom.
Rares Stanciu 0002, Paul Y. Oh
ICRA1
2002 Designing visually servoed tracking to augment camera teleoperators
abstract
There are many features to take into consideration when designing servoed vision for robot control, especially if there are redundant degrees-of-freedom (DOF). When human teleoperated platforms like rovers, booms, gantries, aircraft and submersibles are involved, visual-servoing is particularly challenging. Along with the kinematics and dynamics characteristics in the robot DOF one must consider the human-in-the-loop. Another factor that must be considered is potential motion conflicts arising from the shared man-machine control of the camera and can lead to unstable performance. When the DOF are redundant, the tracking problem becomes more complicated because there are many ways to perform tracking. This paper illustrates these issues and suggests control approaches to resolve them.
Rares Stanciu 0002, Paul Y. Oh
IROS1