EDBT 2026 Demo / reviewers in the wild / expert
Sven R. Schepp
dblp:324/6197
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021
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 |
Video understanding and tracking · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking
human motion prediction |
0.6 | 1 | 2022 | SaRA: A Tool for Safe Human-Robot Coexistence and Collaboration through Reachability Analysis · ICRA 2022 |
Human-robot interaction › safe human-robot interaction
safe human-robot coexistence |
0.6 | 1 | 2022 | SaRA: A Tool for Safe Human-Robot Coexistence and Collaboration through Reachability Analysis · ICRA 2022 |
Methods — techniques the papers use, named apart from their topics
set-based reachability analysis · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | SaRA: A Tool for Safe Human-Robot Coexistence and Collaboration through Reachability AnalysisabstractCurrent safety mechanisms implementing industry standards for human-robot coexistence separate humans and robots through caging. Other approaches allowing humans to enter the workspace of manipulators do not provide formal safety guarantees. Thus, this study aims to facilitate the widespread adoption of collaborative robots by presenting SaRA, an extensible tool that performs set-based reachability analysis and formally guarantees safety. Our experimental results show that the set-based prediction of a human can be computed in a few microseconds, using SaRA, allowing for real-time consideration of many surrounding humans in an environment. Sven R. Schepp, Jakob Thumm, Stefan B. Liu, Matthias Althoff |
ICRA | 1 |