EDBT 2026 Demo / reviewers in the wild / expert
Donald G. Krantz
dblp:94/86
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 first-authorSystems, architecture and hardware · 3 · 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
3 papers |
Legged, aerial and field robots · 56% Multi-agent systems · 28% Robot navigation and mapping · 16% | |
| Computer networks
1 paper |
Wireless networking · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
field robotics |
0.1 | 2 | 2000 | Active Video System for a Miniature Reconnaissance Robot · ICRA 2000 A Miniature Robotic System for Reconnaissance and Surveillance · ICRA 2000 |
Knowledge, reasoning and agents › Multi-agent systems › multi-robot systems
multi-robot team |
0.0 | 1 | 2000 | A Miniature Robotic System for Reconnaissance and Surveillance · ICRA 2000 |
Robotics › Robot navigation and mapping › localization
dead reckoning |
0.0 | 1 | 1996 | Non-uniform dead-reckoning position estimate updates · ICRA 1996 |
Wireless networking › wireless multimedia
wireless video transmission |
0.0 | 1 | 2000 | Active Video System for a Miniature Reconnaissance Robot · ICRA 2000 |
Methods — techniques the papers use, named apart from their topics
pan-tilt mechanism · 0.1CMOS video sensor · 0.1scout deployment · 0.0miniature robot design · 0.0error model · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | A Miniature Robotic System for Reconnaissance and SurveillanceabstractPresents a miniature robotic system ("scout") useful for reconnaissance and surveillance missions. A large number of scout robots are deployed and controlled by humans and/or larger "ranger" robots. The specially designed and constructed scouts are extremely small (roughly 116cc volume) yet are readily deployable (by tossing or launching), have multiple mobility modes, have multiple sensing capabilities, can transmit and receive data and instructions, and have a limited capability for autonomous action. The rangers are significantly larger vehicles, based on a commercial-off-the-shelf platform, augmented with scout launchers, radios, and additional sensors. Together, the scouts and rangers form a hierarchical team capable of carrying out complex missions in a wide variety of environments. Dean F. Hougen, Saifallah Benjaafar, Jordan Bonney, John Budenske, Mark Dvorak, Maria L. Gini, Howard French, Donald G. Krantz, Perry Y. Li, Fred Malver, Bradley J. Nelson, Nikolaos Papanikolopoulos, Paul E. Rybski, Sascha Stoeter, Richard M. Voyles, Kemal Berk Yesin |
ICRA | 8 |
| 2000 | Active Video System for a Miniature Reconnaissance RobotabstractIn this paper we present an active video module that consists of a miniature video sensor, a wireless video transmitter and a pan-tilt mechanism driven by micromotors. The video module is part of a miniature mobile robot that is projected to areas of the environment to be surveyed. A single-chip CMOS video sensor and miniature brushless DC gearmotors are used to comply with restrictions imposed by the robotic system in terms of payload weight volume and power consumption. Different types of actuation are analyzed for compatibility with a mesoscale robotic system. Applications of an active video module are discussed. Kemal Berk Yesin, Bradley J. Nelson, Nikolaos Papanikolopoulos, Richard M. Voyles, Donald G. Krantz |
ICRA | 5 |
| 1996 | Non-uniform dead-reckoning position estimate updatesabstractWe present an error model for dead-reckoning position estimating systems used in robotic research. This model is suitable for use in real time with general position estimating systems when the model is updated throughout the trajectory. A technique for updating the system error model when the position estimate correction information is non-uniform is also described. We have used this error model to screen noisy position corrections to a dead-reckoning navigator. An autonomous robot system using the error model and a compatible position updating technique has been demonstrated both in simulation and in several types of uncontrolled and unstructured environments. Donald G. Krantz, Maria L. Gini |
ICRA | 1 |