A spiking neural network built using memtransistors can help prevent collisions between autonomous vehicles at night. Almost half of fatal accidents occur at night. As vehicles become autonomous, the ways of detecting and avoiding these collisions must evolve too, but current systems are often complicated, resource-intensive or work poorly in the dark.
Intel and Daedalean have developed the first multi-core reference design for certifiable avionics using machine learning, or ML. The design provides vision-based situational awareness using neural networks with high-resolution, high-throughput camera inputs based on Intel’s 11th Gen Core i7 and Agilex F-Series FPGAs.
UAV Navigation has developed a model-agnostic hardware-in-the-loop (HiL) simulator that...
Elythor has developed a UAV that can adapt its wing shape to wind conditions and flight position...
A coil-powered robot fish could make underwater uncrewed systems easier to develop...
TDK has developed a high-stability and vibration-tolerant digital MEMS gyroscope for dynamic...
Researchers in Germany have created an algorithm they say can handle the ethical requirements...
Echodyne’s radar system has been added to a single integrated operating picture (SIOP) platform...
A UK company has developed an electric ducted fan (EDF) motor with a specialist blade...
Skydweller Aero has completed the first autonomous flight of its solar-powered aircraft...