[HTML][HTML] Self-supervised prediction of the intention to interact with a service robot
A service robot can provide a smoother interaction experience if it has the ability to
proactively detect whether a nearby user intends to interact, in order to adapt its behavior eg …
proactively detect whether a nearby user intends to interact, in order to adapt its behavior eg …
Transvisdrone: Spatio-temporal transformer for vision-based drone-to-drone detection in aerial videos
Drone-to-drone detection using visual feed has crucial applications, such as detecting drone
collisions, detecting drone attacks, or coordinating flight with other drones. However, existing …
collisions, detecting drone attacks, or coordinating flight with other drones. However, existing …
Robust real-time AUV self-localization based on stereo vision-inertia
Autonomous underwater vehicles (AUVs) play an important role in deep-sea exploration, in
which AUV self-localization is a key component. However, due to poor visibility caused by …
which AUV self-localization is a key component. However, due to poor visibility caused by …
That sounds right: Auditory self-supervision for dynamic robot manipulation
Learning to produce contact-rich, dynamic behaviors from raw sensory data has been a
longstanding challenge in robotics. Prominent approaches primarily focus on using visual …
longstanding challenge in robotics. Prominent approaches primarily focus on using visual …
Visual servoing with geometrically interpretable neural perception
An increasing number of nonspecialist robotic users demand easy-to-use machines. In the
context of visual servoing, the removal of explicit image processing is becoming a trend …
context of visual servoing, the removal of explicit image processing is becoming a trend …
Self-Supervised Learning of Visual Robot Localization Using LED State Prediction as a Pretext Task
We propose a novel self-supervised approach for learning to visually localize robots
equipped with controllable LEDs. We rely on a few training samples labeled with position …
equipped with controllable LEDs. We rely on a few training samples labeled with position …
Learning to Estimate the Pose of a Peer Robot in a Camera Image by Predicting the States of its LEDs
We consider the problem of training a fully convolutional network to estimate the relative 6D
pose of a robot given a camera image, when the robot is equipped with independent …
pose of a robot given a camera image, when the robot is equipped with independent …
Training on the Fly: On-Device Self-Supervised Learning Aboard Nano-Drones Within 20mW
Miniaturized cyber-physical systems (CPSs) powered by tiny machine learning (TinyML),
such as nano-drones, are becoming an increasingly attractive technology. Their small form …
such as nano-drones, are becoming an increasingly attractive technology. Their small form …
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks
A vision-based drone-to-drone detection system is crucial for various applications like
collision avoidance, countering hostile drones, and search-and-rescue operations …
collision avoidance, countering hostile drones, and search-and-rescue operations …
On-device Self-supervised Learning of Visual Perception Tasks aboard Hardware-limited Nano-quadrotors
Sub-\SI {50}{\gram} nano-drones are gaining momentum in both academia and industry.
Their most compelling applications rely on onboard deep learning models for perception …
Their most compelling applications rely on onboard deep learning models for perception …