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Shane A. Migliore

dblp:60/1222 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › impedance control
joint stiffness control
0.112005
Biologically Inspired Joint Stiffness Control · ICRA 2005
Robotics › Motion planning and robot control
robot control
0.112005
Biologically Inspired Joint Stiffness Control · ICRA 2005
Robotics › Robot manipulation › actuator design › compliant actuator
series elastic actuator
0.012005
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
YearPublicationVenuePosition
2005 Biologically Inspired Joint Stiffness Control
abstract
Biological 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
ICRA1