Demo Data from EDBT 2026 / reviewers in the wild / expert
A. Jaganathan
dblp:35/5395
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2003
—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.
| Computer graphics and multimedia
1 paper |
Computational fabrication · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational fabrication
machining |
0.0 | 1 | 2003 | An error restraining method for accurate freeform surface cutting · ICRA 2003 |
Computational fabrication
tool path generation |
0.0 | 1 | 2003 | An error restraining method for accurate freeform surface cutting · ICRA 2003 |
Methods — techniques the papers use, named apart from their topics
feedback control · 0.0adaptive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | An error restraining method for accurate freeform surface cuttingabstractProducing sculptured surfaces of special parts always poses challenges to machining industry. In this paper, an effective tool path error restraining method utilizing adaptive rules for cutting control is proposed for freeform surface machining. Based on the proposed approach an experimental verification is accomplished in milling a sample part with curved surfaces. Specifically, the parametric spatial curves representing the part's sculptured surface are approximated by sequences of connected line segments. From the current reference point of the cutting tool, the method has the capability of predicting the next reference point of the tool for a given feed. If the predicted position is not within the required tolerance, the algorithm will automatically adjust the position of the cutter so as to satisfy the tolerance requirements using feedback control philosophy. It is proved that the developed adaptive cutting laws are robust in achieving the desired freeform surface cutting with pre-specified tolerance requirements. The given tolerance is measured as the angular deviations to which the generated tool path deviates from the desired profile. Feedrate variations have been implemented in the investigation in the range between 5 mm/second and 30 mm/second. The tool paths generated with and without the adaptive mechanisms are compared. The experimental results demonstrate that the proposed tolerance feedback mechanism is very effective for producing parts having curved surfaces. A. Jaganathan, Yueh-Jaw Lin |
ICRA | 1 |