Demo Data from EDBT 2026 / reviewers in the wild / expert
Jeff Hyams
dblp:46/5874
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 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
2 papers |
Robot navigation and mapping · 84% 3D vision · 11% Motion planning and robot control · 6% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
docking |
0.0 | 1 | 2001 | Low-order-complexity vision-based docking · IEEE Trans. Robotics Autom. 2001 |
Robotics › Robot navigation and mapping › docking
vision-based docking |
0.0 | 1 | 2001 | Low-order-complexity vision-based docking · IEEE Trans. Robotics Autom. 2001 |
Computer vision › 3D vision › multimodal perception
LiDAR-camera fusion |
0.0 | 1 | 2006 | People Tracking and Following with Mobile Robot using an Omnidirectional Camera and a Laser · ICRA 2006 |
Robotics › Robot navigation and mapping
sensor fusion |
0.0 | 1 | 2006 | People Tracking and Following with Mobile Robot using an Omnidirectional Camera and a Laser · ICRA 2006 |
Robotics › Motion planning and robot control › robot control › behavior-based control
reactive behavior |
0.0 | 1 | 2001 | Low-order-complexity vision-based docking · IEEE Trans. Robotics Autom. 2001 |
Methods — techniques the papers use, named apart from their topics
visual tracking · 0.1omnidirectional camera · 0.1laser range finder · 0.1region statistics · 0.0imprinting · 0.0color segmentation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | People Tracking and Following with Mobile Robot using an Omnidirectional Camera and a LaserabstractThe paper presents two different methods for mobile robot tracking and following of a fast-moving person in outdoor unstructured and possibly dynamic environment. The robot is equipped with laser range-finder and omnidirectional camera. The first method is based on visual tracking only and while it works well at slow speeds and controlled conditions, its performance quickly degrades as conditions become more difficult. The second method which uses the laser and the camera in conjunction for tracking performs well in dynamic and cluttered outdoor environments as long as the target occlusions and losses are temporary. Experimental results and analysis are presented for the second approach Marin Kobilarov, Gaurav S. Sukhatme, Jeff Hyams, Parag H. Batavia |
ICRA | 3 |
| 2001 | A Case Study of How Mobile Robot Competitions Promote Future Research
Jennifer Casper, Mark Micire, Jeff Hyams, Robin R. Murphy |
RoboCup | 3 |
| 2001 | Low-order-complexity vision-based dockingabstractThis paper reports on a reactive docking behavior which uses a vision algorithm that grows linearly with the number of image pixels. The docking robot imprints (initializes) on a two-colored docking fiducial upon departing from the dock, then uses region statistics to adapt the color segmentation in changing lighting conditions. The docking behavior was implemented on a marsupial team of robots, where a daughter micro-rover had to reenter the mother robot from an approach zone with a 2 m radius and 140/spl deg/ angular width with a tolerance of /spl plusmn/5 and /spl plusmn/2 cm. Testing during outdoor conditions (noon, dusk) and challenging indoor scenarios (flashing lights) showed that using adaptation and imprinting was more robust than using imprinting atone. Brian W. Minten, Robin R. Murphy, Jeff Hyams, Mark Micire |
IEEE Trans. Robotics Autom. | 3 |