Demo Data from SIGIR 2026 / reviewers in the wild / expert
Michael Weis
dblp:36/6219
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › mechanical design › compliant mechanism design
compliant joint mechanism |
0.1 | 1 | 2010 | On joint design with intrinsic variable compliance: derivation of the DLR QA-Joint · ICRA 2010 |
Robotics › Robot manipulation
actuation |
0.0 | 1 | 2010 | On joint design with intrinsic variable compliance: derivation of the DLR QA-Joint · ICRA 2010 |
Robotics › Robot manipulation › actuation
elastic energy storage |
0.0 | 1 | 2010 | On joint design with intrinsic variable compliance: derivation of the DLR QA-Joint · ICRA 2010 |
Methods — techniques the papers use, named apart from their topics
intrinsic compliance · 0.1elastic energy · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | On joint design with intrinsic variable compliance: derivation of the DLR QA-JointabstractIn this paper we introduce a classification of intrinsically compliant joint mechanisms. Furthermore, we outline design considerations for realizing such devices in order to match the requirements for robust and performant actuation. Based on this elaboration, a new design concept is presented, the DLR QA-Joint. Its performance is investigated by various experiments, covering velocity increase using the elastic energy, joint protection capabilities, and control performance. Oliver Eiberger, Sami Haddadin, Michael Weis, Alin Albu-Schäffer, Gerd Hirzinger |
ICRA | 3 |