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Listening out for sirens

Microphones from Infineon Technologies are being used to detect the sirens of emergency vehicles to ensure that autonomous cars move out of their way.

Platform One

SDR resists interference

Atlas has developed a software-defined radio (SDR) module for UAVs with a reliable anti-interference mode. The 3W radio module supports frequency hopping as a key part of the anti-jamming algorithm in UAVs. It measures 31 x 37 x 4 mm and weighs only 7 g.

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AI system detects UXBs

The system uses large, unlabelled survey datasets to aid automatic...

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Spot the dog’s survey skill

Trimble has teamed up with Exyn Technologies to develop an autonomous robotic system that can be used for surveying complex environments where existing positioning technologies won’t work.

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AI rivals human drivers

Researchers in Germany have developed an autonomous AI system that is comparable to a human driver for detecting pedestrians and other road users.

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‘SuperGPS’ for urban roads

Researchers have developed an alternative positioning system using mobile phone networks and an atomic clock that is more robust and accurate than satnav in urban settings.

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Wi-fi loophole warning

Researchers in Canada have developed a UAV that can use wi-fi signals to see through walls. The device, nicknamed Wi-Peep, can fly near a building and identify and locate all the wi-fi-enabled devices inside it in a matter of seconds.

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Neural net nano-UAVs

A group of researchers has developed neural network algorithms that can work on nano-UAVs weighing as little as 10 g. The nano-UAVs are increasingly useful for monitoring applications, but struggle with complex autonomous operations with multiple objectives.

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Fast, low-power vision

Rather than using general-purpose high-performance vision processors for autonomous vehicles, Recogni and Renesas have developed an embedded platform, which can deliver up to 2000 TOPS.

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Data memory boost bid

A project called Memtonomy at Fraunhofer IESE, Germany, is aiming to tackle the memory storage challenge in driverless vehicles. The constantly growing use of sensors and AI components in driverless cars is creating the need for large amounts of data to be recorded, merged and analysed in real time.