Demo Data from SIGIR 2026 / reviewers in the wild / expert
Konrad Braun
dblp:139/4885
· DBLP profile ↗
2ranked-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 · 1Applied, interdisciplinary, general and emerging computing · 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
2 papers |
Motion planning and robot control · 78% Robot manipulation · 22% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Integrated circuit design · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › disturbance rejection
friction compensation |
0.0 | 2 | 1987 | Adaptive friction compensation in dc-motor drives · IEEE J. Robotics Autom. 1987 Adaptive friction compensation in DC motor drives · ICRA 1986 |
Robotics › Motion planning and robot control › robot control
adaptive control |
0.0 | 1 | 1986 | Adaptive friction compensation in DC motor drives · ICRA 1986 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1986 | Adaptive friction compensation in DC motor drives · ICRA 1986 |
Integrated circuit design
electric motor drives |
0.0 | 1 | 1986 | Adaptive friction compensation in DC motor drives · ICRA 1986 |
Methods — techniques the papers use, named apart from their topics
linear controller design · 0.0adaptive friction compensation · 0.0linear regulator design · 0.0adaptive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1987 | Adaptive friction compensation in dc-motor drivesabstractA control scheme is proposed where the nonlinear effects of friction are compensated adaptively. When the friction is compensated, the motor drive can approximately be described by a constant coefficient linear model. Standard methods can be applied to design a regulator for such a model. This results in a control law which is a combination of a fixed linear controller and an adaptive part which compensates for nonlinear friction effects. Experiments have clearly shown that both static and dynamic friction have nonsymmetric characteristics. They depend on the direction of motion. This is considered in the design of the adaptive friction compensation. The proposes scheme has been implemented and tested on a laboratory prototype with good results. The control law is implemented on an IBM PC. The ideas, algorithm, and experimental results are described. The results are relevant for many precision drives, such as those found in industrial robots. Carlos Canudas-de-Wit, Karl Johan Åström, Konrad Braun |
IEEE J. Robotics Autom. | 3 |
| 1986 | Adaptive friction compensation in DC motor drivesabstractThis paper proposes a control scheme where the nonlinear effects of friction are compensated adaptively. When the friction is compensated the motor drive can approximately be described by a constant coefficient linear model. Standard methods can be applied to design a regulator for such a model. This results in a control law which is a combination of a fixed linear controller and an adaptive part which compensates for nonlinear friction effects. Experiments have clearly shown that both static and dynamic friction have nonsymmetric characteristic. They depend on the direction of motion. This is considered in the design of the adaptive friction compensation. The proposed scheme has been implemented and tested on a laboratory prototype with good results. The control low is implemented on an IBM-PC. The paper describes the ideas, the algorithm and the experimental results. The results are relevant for many precision drives like those found in industrial robots. Carlos Canudas-de-Wit, Karl Johan Åström, Konrad Braun |
ICRA | 3 |