Demo Data from EDBT 2026 / reviewers in the wild / expert
B. J. Ulrich
dblp:231/3108
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1990
—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 |
Motion planning and robot control · 77% Robot manipulation · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › contact control › contact task control
robot force control |
0.0 | 1 | 1990 | Robotic grinding force regulation: design, implementation and benefits · ICRA 1990 |
Robotics › Robot manipulation › industrial robot
grinding robot |
0.0 | 1 | 1990 | Robotic grinding force regulation: design, implementation and benefits · ICRA 1990 |
Methods — techniques the papers use, named apart from their topics
force feedback · 0.0PID control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Robotic grinding force regulation: design, implementation and benefitsabstractThe design and implementation of force control for robotic rigid disk grinding are described. Experiments were conducted using a PUMA 762/VAL II industrial robot equipped with a 4-hp pneumatic grinder and a JR/sup 3/ force sensor. An external, 386-based host microcomputer, communicating with VAL II online, performs the force control algorithm calculations. The robotic grinding force model used was an experimentally verified analytic model. It was found that the grinding forces are very sensitive to the robot arm stiffness. Also, the end-effector path tracking errors, caused by the limited accuracy of the PUMA robot, significantly affect the grinding forces. The experimental results show, however, that a finely tuned PID force-feedback controller is able to maintain the grinding forces at a specified value. It can effectively compensate for force errors caused by both step force disturbances and robot path-tracking errors. The benefits of such force control are demonstrated by improved profiles of finished workpieces.> Li Liu 0019, B. J. Ulrich, Mohamed A. Elbestawi |
ICRA | 2 |