Demo Data from SIGIR 2026 / reviewers in the wild / expert
Deborah K. Tissue
dblp:129/8900
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1990
—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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
adaptive control |
0.0 | 1 | 1990 | Adaptive control for mechanical manipulators having a joint compliance · ICRA 1990 |
Robotics › Motion planning and robot control › manipulator control
compliant joint control |
0.0 | 1 | 1990 | Adaptive control for mechanical manipulators having a joint compliance · ICRA 1990 |
Methods — techniques the papers use, named apart from their topics
pole placement · 0.0parameter adaptation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Adaptive control for mechanical manipulators having a joint complianceabstractAn approach to the robust position and velocity control of mechanical manipulators having a joint compliance is presented. A control model of such a manipulator is derived by linearizing the nonlinear equations about a desired trajectory. This control model is described by multivariable difference equations. The parameters of the model are estimated by parameter-adaptation algorithms. Control gains, determined from the control model by using the pole-placement technique, are computed online with the estimates of the system parameters. Simulation results with a two-link mechanical manipulator are presented to show the effectiveness of the approach.> J. Yuh, Deborah K. Tissue |
ICRA | 2 |