Demo Data from SIGIR 2026 / reviewers in the wild / expert
Manuel Lussi
dblp:226/6334
· DBLP profile ↗
1ranked-venue papers
1as 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 · 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 |
Robot navigation and mapping · 50% 3D vision · 50% | |
| Computer graphics and multimedia
1 paper |
Computational fabrication · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
localization |
0.3 | 1 | 2018 | Accurate and Adaptive in Situ Fabrication of an Undulated Wall Using an on-Board Visual Sensing System · ICRA 2018 |
Computer vision › 3D vision › pose estimation
visual pose estimation |
0.3 | 1 | 2018 | Accurate and Adaptive in Situ Fabrication of an Undulated Wall Using an on-Board Visual Sensing System · ICRA 2018 |
Computational fabrication › computer-aided manufacturing
robotic fabrication |
0.3 | 1 | 2018 | Accurate and Adaptive in Situ Fabrication of an Undulated Wall Using an on-Board Visual Sensing System · ICRA 2018 |
Methods — techniques the papers use, named apart from their topics
vision-based sensing · 0.7CAD model referencing · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Accurate and Adaptive in Situ Fabrication of an Undulated Wall Using an on-Board Visual Sensing SystemabstractIn this paper we present a system for the in situ33In the context of building construction, “in situ” means that fabrication takes place at the structure's final location directly on the building site. fabrication of a full-scale, load-bearing, and doubly-curved steel reinforced concrete wall. Two complementary vision-based sensing systems provide the feedback necessary to build a 12 meter long steel wire mesh as part of a novel digital building process. The sensing systems provide estimates of the robot pose, referenced to the CAD model of the building site, as well as feedback on the accuracy of the built structure over the course of construction. This second piece of information is used to adapt the building plan to compensate for system inaccuracies and material deformations which occur during buildup. In this way, the structure was successfully built with 98% of the total geometry within 2 centimeters of the designed position. To the best of our knowledge, this is the largest structure which has been built by a mobile robot using solely vision-based sensing. Manuel Lussi, Timothy Sandy, Kathrin Dörfler, Norman Hack, Fabio Gramazio, Matthias Kohler, Jonas Buchli |
ICRA | 1 |