Demo Data from SIGIR 2026 / reviewers in the wild / expert
Shane A. Migliore
dblp:60/1222
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 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
1 paper |
Motion planning and robot control · 87% Robot manipulation · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › impedance control
joint stiffness control |
0.1 | 1 | 2005 | Biologically Inspired Joint Stiffness Control · ICRA 2005 |
Robotics › Motion planning and robot control
robot control |
0.1 | 1 | 2005 | Biologically Inspired Joint Stiffness Control · ICRA 2005 |
Robotics › Robot manipulation › actuator design › compliant actuator
series elastic actuator |
0.0 | 1 | 2005 | Biologically Inspired Joint Stiffness Control · ICRA 2005 |
Methods — techniques the papers use, named apart from their topics
open-loop control · 0.1antagonistic actuation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Biologically Inspired Joint Stiffness ControlabstractBiological systems are able to perform movements in unpredictable environments more elegantly than traditionally engineered robotic systems. A current limitation of robotic systems is their inability to simultaneously and independently control both joint angle and joint stiffness without electromechanical feedback loops, which can reduce system stability. In this paper, we describe the development and physical implementation of a servo-actuated robotic joint that uses antagonistic, series-elastic actuation with novel nonlinear spring mechanisms. These mechanisms form a real-time mechanical feedback loop that provides the joint with angle and stiffness control through differential and common-mode actuation of the servos, respectively. This approach to joint control emulates the mechanics of antagonistic muscle groups used by animals, and we experimentally show that it is capable of independently controlling both joint angle and joint stiffness using a simple open-loop control algorithm. Shane A. Migliore, Edgar A. Brown, Stephen P. DeWeerth |
ICRA | 1 |