Demo Data from SIGIR 2026 / reviewers in the wild / expert
Craig R. Carnigan
dblp:231/3160
· DBLP profile ↗
1ranked-venue papers
1as 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 · 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.
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 3, 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
adaptive tracking control |
0.0 | 1 | 1990 | Adaptive tracking for complex systems using reduced-order models · ICRA 1990 |
Robotics › Motion planning and robot control › dynamic modeling
reduced-order model |
0.0 | 1 | 1990 | Adaptive tracking for complex systems using reduced-order models · ICRA 1990 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1990 | Adaptive tracking for complex systems using reduced-order models · ICRA 1990 |
Methods — techniques the papers use, named apart from their topics
parameter adaptive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Adaptive tracking for complex systems using reduced-order modelsabstractReduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track a payload trajectory using a four-parameter model instead of the full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory. The adaptive controller was able to reduce tracking errors substantially over the constant gain approach for cases where the payload began to dominate the system dynamics. This meant that even when only slight perturbations to the four-parameter model used by the controller were present, the adaptive controller could reduce the tracking errors significantly, as if a full-order model were being used.> Craig R. Carnigan |
ICRA | 1 |