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Joseph Hart

dblp:37/2951 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—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
Legged, aerial and field robots · 68% Robot navigation and mapping · 16% Motion planning and robot control · 16%

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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
humanoid robot
0.112008
CB: Exploring neuroscience with a humanoid research platform · ICRA 2008
Robotics › Robot navigation and mapping › active perception
active object recognition
0.012008
CB: Exploring neuroscience with a humanoid research platform · ICRA 2008
Robotics › Legged, aerial and field robots › legged robots › legged robot locomotion
bipedal locomotion
0.012008
CB: Exploring neuroscience with a humanoid research platform · ICRA 2008
Robotics › Motion planning and robot control › locomotion control
central pattern generator
0.012008
CB: Exploring neuroscience with a humanoid research platform · ICRA 2008

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

compliance controller · 0.1
YearPublicationVenuePosition
2008 CB: Exploring neuroscience with a humanoid research platform
abstract
In this video presentation we introduce a 50 degrees of freedom humanoid robot, CB -ComputationalBrain[1]. CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real world contexts, as humans do. In so doing, we focus on utilising a system that is closer to humans - in sensing, kinematics configuration and performance. We present a full-body compliance controller that was developed for the motion control of our humanoid robot [2]. Our initial experimentation on our system includes: 1) full-body compliant control - physical interactions/balancing/motion control; 2) the integrated visual ocular-motor responses; 3) perception and control - reaching, foveation, and active object recognition; 4) our studies of Central Pattern Generator for walking.
Gordon Cheng, Sang-Ho Hyon, Ales Ude, Jun Morimoto, Joshua G. Hale, Joseph Hart, Jun Nakanishi, Darrin C. Bentivegna, Jessica K. Hodgins, Christopher G. Atkeson, Michael N. Mistry, Stefan Schaal, Mitsuo Kawato
ICRA6