Demo Data from EDBT 2026 / reviewers in the wild / expert
Steve Jordan
dblp:81/3389
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1988
—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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 100% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures › domain-specific accelerator
application-specific processor |
0.0 | 1 | 1988 | Design and simulation of RIPS: an advanced robot control system · ICRA 1988 |
Robotics › Motion planning and robot control › robot control › model-based control
computed torque control |
0.0 | 1 | 1988 | Design and simulation of RIPS: an advanced robot control system · ICRA 1988 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1988 | Design and simulation of RIPS: an advanced robot control system · ICRA 1988 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.0interprocessor communication · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Design and simulation of RIPS: an advanced robot control systemabstractThe design and simulation of RIPS, a robotic instruction processing system, are discussed. The authors are building a prototype version of RIPS which will be used as a general research tool to study problems of robot control. The architecture of RIPS is geared for robot control, yet the system is general and fully programmable and does not assume any manipulator characteristics. There is sufficient computing capacity to address any of several important automation problems such as force control, multiple manipulator coordination, or manufacturing cell-level control. Simulations show that using RIPS to control a Stanford manipulator with the computed torque method gives an update rate of 255 mu s. This simulation includes all interprocessor communication as well as the computing time necessary for equation evaluation.> Steven E. Butner, Yulun Wang, Amante Mangaser, Steve Jordan |
ICRA | 4 |