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Sophie Oustrieres

dblp:97/8365 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—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 · 67% 3D vision · 33%

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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
aerial robot control
0.112010
A general optical flow based terrain-following strategy for a VTOL UAV using multiple views · ICRA 2010
Computer vision › 3D vision › motion estimation
optical flow
0.112010
A general optical flow based terrain-following strategy for a VTOL UAV using multiple views · ICRA 2010
Robotics › Legged, aerial and field robots › vehicle guidance
terrain following
0.112010
A general optical flow based terrain-following strategy for a VTOL UAV using multiple views · ICRA 2010

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

optical flow · 0.1nonlinear control · 0.1multiple views · 0.1
YearPublicationVenuePosition
2010 A general optical flow based terrain-following strategy for a VTOL UAV using multiple views
abstract
This paper presents a general approach for terrain following (including obstacle avoidance) of a vertical take-off and landing vehicle (VTOL) using multiple observation points. The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera, IMU and barometric altimeter), manoeuvering over a textured rough terrain made of a concatenation of planar surfaces. Assuming that the forward velocity is separately regulated to a desired non-zero value, the proposed control approach ensures terrain following and guarantees the vehicle does not collide with obstacles during the task. The proposed control acquires an optical flow from multiple spatially separate observation points, typically obtained via multiple cameras or non collinear directions in a unique camera. The proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor UAV to demonstrate the performance of the closed loop system.
Bruno Hérissé, Sophie Oustrieres, Tarek Hamel, Robert E. Mahony, François-Xavier Russotto
ICRA2