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July 13, 2021

US DARPA selects research teams for Invisible Headlights programme

Invisible Headlights programme seeks to determine if autonomous vehicles can navigate in dark using passive sensors.

The Defense Advanced Research Projects Agency (DARPA) in the US has selected four industry and university research teams to advance with the Invisible Headlights programme.

The selected teams will work with DARPA in the project that seeks to determine if autonomous vehicles can navigate in absence of light using passive sensors.

Current systems require active illumination to traverse at night, which increases the risk of detection by adversaries. The Invisible Headlights programme was conceived to address this vulnerability.

The programme aims to transform the ambient thermal light present in all environments into a totally passive 3D sensor to support autonomous navigation.

Under the programme, Areté Associates will conduct virtual analyses to assess the ambient spectral and polarimetric infrared environment and develop low-contrast-capable 3D vision algorithms.

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Kitware is tasked to estimate local 3D scene structure and semantics for navigation, while Purdue University will be developing new ultrafast, spin-based sensors and 3D vision approaches using ambient thermal environment properties.

A Massachusetts Institute of Technology (MIT) team is engaged to scale superconducting nanowire single-photon detector (SNSPD) technology into a very low noise infrared sensing array.

DARPA Defense Sciences Office Invisible Headlights programme manager Joe Altepeter said: “These teams are pursuing innovative approaches to exploit the infrared spectrum.

“They are exploring ways to capture more scene information using new devices, improved algorithms, and increased measurement diversity.”

A government team led by the army C5ISR Center’s Night Vision and Electronic Sensors Directorate (NVESD) is also associated with the project.

During Phase I, the research teams will assess the feasibility of using information from thermal emissions to enable autonomous driving in very dark conditions.

In the subsequent phase, the teams will develop and test sensors and algorithms to demonstrate that real systems can measure enough information for 3D vision.

The final stage will involve building and trialling passive demonstration systems for field tests.

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