Baoquan Song

dblp:80/6276 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2011
—ORCID · conflict

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

Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 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% Legged, aerial and field robots · 13%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › sensor-based control › visual servoing
uncalibrated visual servoing
0.112011
Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments · Sci. China Inf. Sci. 2011
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.112011
Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments · Sci. China Inf. Sci. 2011
Robotics › Legged, aerial and field robots › aerial robots
autonomous helicopter
0.012011
Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments · Sci. China Inf. Sci. 2011

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

dynamic visual servoing · 0.1
YearPublicationVenuePosition
2011 Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments
Caizhi Fan, Yun-Hui Liu 0001, Baoquan Song, Dongxiang Zhou
Sci. China Inf. Sci.3
2009 Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments
abstract
This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique but differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depth of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of the image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performance of the proposed method.
Caizhi Fan, Baoquan Song, Xuanping Cai, Yun-Hui Liu 0001
IROS2
2006 Depth Perception of the Surfaces in Occluded Scenic Images
Baoquan Song, Zhengzhi Wang
ICONIP (2)1
2004 A New Computational Model of Biological Vision for Stereopsis
Baoquan Song, Zongtan Zhou, Dewen Hu, Zhengzhi Wang
ISNN (2)1