Demo Data from EDBT 2026 / reviewers in the wild / expert
Joseph Hart
dblp:37/2951
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—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 |
Legged, aerial and field robots · 68% Robot navigation and mapping · 16% Motion planning and robot control · 16% |
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
humanoid robot |
0.1 | 1 | 2008 | CB: Exploring neuroscience with a humanoid research platform · ICRA 2008 |
Robotics › Robot navigation and mapping › active perception
active object recognition |
0.0 | 1 | 2008 | CB: Exploring neuroscience with a humanoid research platform · ICRA 2008 |
Robotics › Legged, aerial and field robots › legged robots › legged robot locomotion
bipedal locomotion |
0.0 | 1 | 2008 | CB: Exploring neuroscience with a humanoid research platform · ICRA 2008 |
Robotics › Motion planning and robot control › locomotion control
central pattern generator |
0.0 | 1 | 2008 | CB: Exploring neuroscience with a humanoid research platform · ICRA 2008 |
Methods — techniques the papers use, named apart from their topics
compliance controller · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | CB: Exploring neuroscience with a humanoid research platformabstractIn this video presentation we introduce a 50 degrees of freedom humanoid robot, CB -ComputationalBrain[1]. CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real world contexts, as humans do. In so doing, we focus on utilising a system that is closer to humans - in sensing, kinematics configuration and performance. We present a full-body compliance controller that was developed for the motion control of our humanoid robot [2]. Our initial experimentation on our system includes: 1) full-body compliant control - physical interactions/balancing/motion control; 2) the integrated visual ocular-motor responses; 3) perception and control - reaching, foveation, and active object recognition; 4) our studies of Central Pattern Generator for walking. Gordon Cheng, Sang-Ho Hyon, Ales Ude, Jun Morimoto, Joshua G. Hale, Joseph Hart, Jun Nakanishi, Darrin C. Bentivegna, Jessica K. Hodgins, Christopher G. Atkeson, Michael N. Mistry, Stefan Schaal, Mitsuo Kawato |
ICRA | 6 |