Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kanzhong Yao
dblp:351/4118
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · unresolved
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 |
Motion planning and robot control · 87% Robot navigation and mapping · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › multi-robot control
leader-follower control |
0.7 | 1 | 2023 | Image-Based Visual Servoing Switchable Leader-follower Control of Heterogeneous Multi-agent Underwater Robot System · ICRA 2023 |
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing |
0.7 | 1 | 2023 | Image-Based Visual Servoing Switchable Leader-follower Control of Heterogeneous Multi-agent Underwater Robot System · ICRA 2023 |
Robotics › Robot navigation and mapping › mobile robot navigation › vehicle navigation
underwater vehicle navigation |
0.2 | 1 | 2023 | Image-Based Visual Servoing Switchable Leader-follower Control of Heterogeneous Multi-agent Underwater Robot System · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
image-based visual servoing · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Image-Based Visual Servoing Switchable Leader-follower Control of Heterogeneous Multi-agent Underwater Robot SystemabstractConfined and cluttered aquatic environments present a number of significant challenges with respect to inspection by robotic platforms, including localisation and communications. Some of these can be mitigated by using collaborative heterogeneous multi-robot teams. An important element of such a system is collaborative control. This paper addresses this challenge by presenting an Image-Based Visual Servoing (IBVS), leader-follower control system for heterogeneous aquatic robots. Experiments were conducted in an uncluttered pond to demonstrate the capabilities of the system. The results show robots can maintain tracking each other with maximum$x$and$y$displacements of 0.42 m and 0.41 m, the maximum projection distance in the xy-plane of maintaining formation is 0.45 m, showing the stability and feasibility of deploying such system on underwater platforms. Kanzhong Yao, Nathalie Bauschmann, Thies L. Alff, Wei Cheah, Daniel-André Duecker, Keir Groves, Ognjen Marjanovic, Simon Watson 0001 |
ICRA | 1 |