Add to ORKGWe suggest the first system that runs real-time semantic segmentation via deep learning on a weak micro-computer such as the Raspberry Pi Zero v2 (whose price was \$15) attached to a toy-drone. In particular, since the Raspberry Pi weighs less than $16$ grams, and its size is half of a credit card, we could easily attach it to the common commercial DJI Tello toy-drone (<\$100, <90 grams, 98 $\times$ 92.5 $\times$ 41 mm). The result is an autonomous drone (no laptop nor human in the loop) that can detect and classify objects in real-time from a video stream of an on-board monocular RGB camera (no GPS or LIDAR sensors). The companion videos demonstrate how this Tello drone scans the lab for people (e.g. for the use of firefighters or security...
Miniaturizing an autonomous robot is a challenging task - not only the mechanical but also the elect...
Internet-of-Things (IoT) devices equipped with temperature and humidity sensors, and cameras are inc...
This paper describes how advanced deep learning based computer vision algorithms are applied to enab...
In this thesis we want to create a deep learning based object detection solution that is able to run...
The evolution of energy-efficient ultra-low-power (ULP) parallel processors and the diffusion of con...
Many emerging applications of nano-sized unmanned aerial vehicles (UAVs), with a few form-factor, re...
Unmanned aerial vehicles, also known as drones, have been more and more widely used in recent decade...
Drones have been widely used in everyday life and they can help deal with various tasks, including p...
This article belongs to the Special Issue Time-Sensitive Networks for Unmanned Aircraft SystemsUnman...
The proliferation of drones around the world was sparked by the reduction in the cost of owning a dr...
This paper proposes a UAV platform that autonomously detects, hunts, and takes down other small UAVs...
Nano-size unmanned aerial vehicles (UAVs), with few centimeters of diameter and sub-10 Watts of tota...
Convolutional neural networks (CNNs) are fueling the advancement of autonomous palm-sized drones, i....
Dynamically changing environments, unreliable state estimation, and operation under severe resource ...
none5siMiniaturizing an autonomous robot is a challenging task - not only the mechanical but also th...
Miniaturizing an autonomous robot is a challenging task - not only the mechanical but also the elect...
Internet-of-Things (IoT) devices equipped with temperature and humidity sensors, and cameras are inc...
This paper describes how advanced deep learning based computer vision algorithms are applied to enab...
In this thesis we want to create a deep learning based object detection solution that is able to run...
The evolution of energy-efficient ultra-low-power (ULP) parallel processors and the diffusion of con...
Many emerging applications of nano-sized unmanned aerial vehicles (UAVs), with a few form-factor, re...
Unmanned aerial vehicles, also known as drones, have been more and more widely used in recent decade...
Drones have been widely used in everyday life and they can help deal with various tasks, including p...
This article belongs to the Special Issue Time-Sensitive Networks for Unmanned Aircraft SystemsUnman...
The proliferation of drones around the world was sparked by the reduction in the cost of owning a dr...
This paper proposes a UAV platform that autonomously detects, hunts, and takes down other small UAVs...
Nano-size unmanned aerial vehicles (UAVs), with few centimeters of diameter and sub-10 Watts of tota...
Convolutional neural networks (CNNs) are fueling the advancement of autonomous palm-sized drones, i....
Dynamically changing environments, unreliable state estimation, and operation under severe resource ...
none5siMiniaturizing an autonomous robot is a challenging task - not only the mechanical but also th...
Miniaturizing an autonomous robot is a challenging task - not only the mechanical but also the elect...
Internet-of-Things (IoT) devices equipped with temperature and humidity sensors, and cameras are inc...
This paper describes how advanced deep learning based computer vision algorithms are applied to enab...