Demo Data from SIGIR 2026 / reviewers in the wild / expert
Theodore E. Djaferis
dblp:120/5772
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1987
—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 |
Robot manipulation · 67% Motion planning and robot control · 33% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
dexterous manipulation |
0.0 | 1 | 1987 | Multivariable feedback control of the JPL/Stanford hand · ICRA 1987 |
Robotics › Robot manipulation › grasping › multifingered hand
multifingered hand control |
0.0 | 1 | 1987 | Multivariable feedback control of the JPL/Stanford hand · ICRA 1987 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1987 | Multivariable feedback control of the JPL/Stanford hand · ICRA 1987 |
Methods — techniques the papers use, named apart from their topics
pole assignment · 0.0linear multivariable feedback control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1987 | Multivariable feedback control of the JPL/Stanford handabstractDexterous hands offer a great deal of flexibility in grasping and manipulation. As such, it can be used as a powerful device for assembly. However, we have to guarantee stable behavior and good performance from the hand and so attention must be focused on control issues. In this paper we deal with the control of the JPL/STANFORD hand. We use kinematic relationships developed earlier and suggest dynamic models for the fingers. We then develop Linear Multivariable Feedback Control strategies which guarantee local stability for controlling one finger. We employ design methods in the frequency domain, based on pole assignment techniques. Controllers are designed for a simple dynamic model and implemented on one finger. Results are presented along with a discussion for future work. S. T. Venkataraman, Theodore E. Djaferis |
ICRA | 2 |