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Varun Asthana

dblp:278/2566 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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
3D vision · 64% Legged, aerial and field robots · 36%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
depth estimation
0.512021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Robotics › Legged, aerial and field robots › rough terrain locomotion
gap crossing
0.512021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Robotics › Legged, aerial and field robots › aerial robots › UAV navigation
quadrotor navigation
0.512021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Computer vision › 3D vision › depth estimation
stereo depth estimation
0.512021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Computer vision › 3D vision › stereo vision
variable baseline stereo
0.512021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Computer vision › 3D vision
camera calibration
0.112021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021
Computer vision › 3D vision › camera calibration
stereo calibration
0.112021
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021

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

on-the-fly baseline adaptation · 0.5interpolation of calibration parameters · 0.5
YearPublicationVenuePosition
2021 MorphEyes: Variable Baseline Stereo For Quadrotor Navigation
abstract
Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem of depth range being limited and dictated by the baseline chosen at design time. In this paper, we present a framework for quadrotor navigation based on a stereo camera system whose baseline can be adapted on-the-fly. We present a method to calibrate the system at a small number of discrete baselines and interpolate the parameters for the entire baseline range. We present an extensive theoretical analysis of calibration and synchronization errors. We showcase three different applications of such a system for quadrotor navigation: (a) flying through a forest, (b) flying through an unknown shaped/location static/dynamic gap, and (c) accurate 3D pose detection of an independently moving object. We show that our variable baseline system is more accurate and robust in all three scenarios. To our knowledge, this is the first work that applies the concept of morphable design to achieve a variable baseline stereo vision system on a quadrotor.
Nitin J. Sanket, Chahat Deep Singh, Varun Asthana, Cornelia Fermüller, Yiannis Aloimonos
ICRA3