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Keegan Wade

dblp:64/973 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—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
Reinforcement learning · 30% Robot manipulation · 30% Motion planning and robot control · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Reinforcement learning
imitation learning
0.012003
Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids · ICRA 2003
Robotics › Motion planning and robot control › robot control
inverse kinematics
0.012003
Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids · ICRA 2003
Robotics › Robot manipulation › learning from demonstration
whole-body motion imitation
0.012003
Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids · ICRA 2003
Robotics › Legged, aerial and field robots › legged robots
humanoid locomotion
0.012003
Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids · ICRA 2003

Methods — techniques the papers use, named apart from their topics

inverse kinematics · 0.03d vision · 0.0
YearPublicationVenuePosition
2003 Enabling real-time full-body imitation: a natural way of m-ansferring human movement to humanoids
abstract
We seek intuitive, efficient ways to create and direct human-like behaviors for humanoid robots. Here we present a method to enable humanoid robots to acquire movements by imitation. The robot uses 3D vision to perceive the movements of a human teacher, and then estimates the teacher's body postures using a fast full-body inverse kinematics method that incorporates a kinematic model of the teacher. This solution is then mapped to the robot and reproduced in real-time. The robustness of the method is tested on a 30-degree-of-freedom Sarcos humanoid robot located at ATR using 3D vision data from external cameras and from head-mounted cameras.
Marcia Riley, Ales Ude, Keegan Wade, Christopher G. Atkeson
ICRA3