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Steven Christensen

dblp:226/6297 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 · 87% Robot navigation and mapping · 13%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › underactuated robotics
acrobot
0.312018
Stickman: Towards a Human Scale Acrobatic Robot · ICRA 2018
Robotics › Robot navigation and mapping
state estimation
0.112018
Stickman: Towards a Human Scale Acrobatic Robot · ICRA 2018

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

laser range finding · 0.3dynamic modeling · 0.3IMU state estimation · 0.3
YearPublicationVenuePosition
2018 Stickman: Towards a Human Scale Acrobatic Robot
abstract
Human performers have developed impressive acrobatic techniques over thousands of years of practicing the gymnastic arts. At the same time, robots have started to become more mobile and autonomous, and can begin to imitate these stunts in dramatic and informative ways. We present a simple two degree of freedom robot that uses a gravity-driven pendulum launch and produces a variety of somersaulting stunts. The robot uses an IMU and a laser range-finder to estimate its state mid-flight and actuates to change its motion both on and and off the pendulum. We discuss the dynamics of this behavior in a framework of acrobatic capability and present experimental results.
Morgan Pope, Steven Christensen, David L. Christensen, Anthony Simeonov, Grant Imahara, Günter Niemeyer
ICRA2