Demo Data from EDBT 2026 / reviewers in the wild / expert
A. Gurman
dblp:206/7033
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
grasping |
0.3 | 1 | 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge · ICRA 2018 |
Robotics › Robot manipulation › grasping
pick-and-place |
0.3 | 1 | 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge · ICRA 2018 |
Robotics › Robot manipulation
warehouse automation |
0.3 | 1 | 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge · ICRA 2018 |
Robotics › Robot manipulation › industrial robot
cartesian robot arm |
0.1 | 1 | 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge · ICRA 2018 |
Robotics › Robot manipulation › robot design
manipulator design |
0.1 | 1 | 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge · ICRA 2018 |
Methods — techniques the papers use, named apart from their topics
experience-centred design · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics ChallengeabstractThe Amazon Robotics Challenge enlisted sixteen teams to each design a pick-and-place robot for autonomous warehousing, addressing development in robotic vision and manipulation. This paper presents the design of our custom-built, cost-effective, Cartesian robot system Cartman, which won first place in the competition finals by stowing 14 (out of 16) and picking all 9 items in 27 minutes, scoring a total of 272 points. We highlight our experience-centred design methodology and key aspects of our system that contributed to our competitiveness. We believe these aspects are crucial to building robust and effective robotic systems. Douglas Morrison, Adam W. Tow, M. McTaggart, Norton Kelly-Boxall, Sean Wade-McCue, Jordan Erskine, R. Grinover, A. Gurman, T. Hunn, Anton Milan, Trung Pham, G. Rallos, A. Razjigaev, T. Rowntree, K. Vijay, Zheyu Zhuang, Chris Lehnert, Ian D. Reid 0001, Peter I. Corke, Jürgen Leitner |
ICRA | 9 |