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Zdravko Balorda

dblp:67/3091 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1994
—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-authorApplied, interdisciplinary, general and emerging computing · 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
2 papers
Robot manipulation · 71% Motion planning and robot control · 19% 3D vision · 10%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
nonprehensile manipulation
0.011994
Reducing positioning uncertainty of objects by robot pushing · IEEE Trans. Robotics Autom. 1994
Robotics › Robot manipulation › nonprehensile manipulation
robotic pushing
0.011994
Reducing positioning uncertainty of objects by robot pushing · IEEE Trans. Robotics Autom. 1994
Robotics › Motion planning and robot control › motion planning › manipulation planning
sensorless manipulation
0.011990
Reducing uncertainty of objects by robot pushing · ICRA 1990
Computer vision › 3D vision
object pose estimation
0.011994
Reducing positioning uncertainty of objects by robot pushing · IEEE Trans. Robotics Autom. 1994
Robotics › Robot manipulation › nonprehensile manipulation
pushing manipulation
0.011990
Reducing uncertainty of objects by robot pushing · ICRA 1990

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

friction modeling · 0.0force analysis · 0.0convex polyhedron contact analysis · 0.0
YearPublicationVenuePosition
1994 Reducing positioning uncertainty of objects by robot pushing
abstract
Robotic applications often involve manipulation of objects where position and orientation are not perfectly known. Pushing an object for instance by a fence, can be employed to accurately align parts, reducing uncertainty to only one degree of freedom. In this paper a pushing task involving two fingers that completely constrains an object in a plane is proposed. The stability of orientation and position of an object being pushed is discussed. The solution obtained is unique despite the fact that the distribution of forces supporting the object cannot, in general, be known. The proposed task of pushing is simple although some preliminary information about the initial position and orientation of an object is required. An approach to avoid the ambiguity in orientation, owing to the effect of friction between the object and the pusher, by introducing up and down movement of the pusher is also presented.>
Zdravko Balorda, Tadej Bajd
IEEE Trans. Robotics Autom.1
1990 Reducing uncertainty of objects by robot pushing
abstract
A sensorless manipulation task eliminating geometrical uncertainty is proposed. It involves a two-fingered tool attached to a robot end effector. The object is assumed to be a convex polyhedron, although this assumption is later relaxed. Assuming that position and orientation are approximately known prior to operation, the initial position of the tool and the direction of movement are chosen. As the tool advances it strikes the object. If the trajectory is chosen properly, the fingers will contact the object with its corner between them. It is shown that such a configuration of contact points uniquely constrains the position of an object in all degrees of freedom.>
Zdravko Balorda
ICRA1