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M. Braae

dblp:139/3758 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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 · 62% Motion planning and robot control · 38%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › bio-inspired robot
bio-inspired robot locomotion
0.212014
Rapid acceleration and braking: Inspirations from the cheetah's tail · ICRA 2014
Robotics › Motion planning and robot control › robot control
feedback control
0.112014
Rapid acceleration and braking: Inspirations from the cheetah's tail · ICRA 2014
Robotics › Motion planning and robot control
robot control
0.112014
Rapid acceleration and braking: Inspirations from the cheetah's tail · ICRA 2014

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

template model · 0.2feedback controller design · 0.2
YearPublicationVenuePosition
2014 Rapid acceleration and braking: Inspirations from the cheetah's tail
abstract
Stimulated by recent biomechanics research of the cheetah, a novel tail controller system for rapid acceleration and braking is presented. To understand the targeted behaviour of a cheetah performing a longitudinal manoeuvre and the effects an actuated tail has, a simple mathematical template was developed. Subsequently feedback controllers were designed based on our hypothesis. Finally, the control system was experimentally tested on a reduced order robot model which increased its manoeuvrability considerably.
Amir Patel, M. Braae
ICRA2
2013 Rapid turning at high-speed: Inspirations from the cheetah's tail
abstract
Inspired by the cheetah, we present a novel tail control system for manoeuvring terrestrial robots at high speed. The mathematic model for a high-speed turn is derived and the model with a tail is shown to be more successful at rapid turns in simulation. We then built a high speed mobile platform with an actuated tail to experimentally validate the control algorithms. Further controller development is performed based on results of the initial simulations. Finally, we show that by rapidly swinging the tail, our system is capable of turning at much higher speeds than a tail-less version.
Amir Patel, M. Braae
IROS2