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

Vladimir Zeman

dblp:99/10901 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1989
—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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › motion planning › real-time motion planning
online trajectory planning
0.011989
On-line robot trajectory planning for catching a moving object · ICRA 1989
Robotics › Motion planning and robot control
trajectory planning
0.011989
On-line robot trajectory planning for catching a moving object · ICRA 1989

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

heuristic search · 0.0
YearPublicationVenuePosition
1989 On-line robot trajectory planning for catching a moving object
abstract
The problem of using a manipulator to catch a moving object without any advanced knowledge of its trajectory is discussed, and a heuristic procedure is proposed. The method is divided into two parts: a coarse tuning algorithm first drives the end effector into the neighborhood of the object in near-minimum time; a finite tuning algorithm then provides precise matching of the object's trajectory to ensure the relative velocity and acceleration at the time of grasping. The resulting sensor-based system is simulated for a two-degree-of-freedom planar robot with a highly nonlinear object path. The approach can rapidly be extended to six-degree-of-freedom manipulators.>
Z. C. Lin, Vladimir Zeman, Rajnikant V. Patel
ICRA2