Autonomous and semi-autonomous systems need active illumination to navigate at night or underground. Switching on visible headlights or some other emitting system like lidar, however, has a significant drawback: It allows adversaries to detect a vehicle’s presence, in some cases from long distances away.
The Invisible Headlights program aims to discover and quantify the available information in ambient thermal emissions, determine how much of that information is useful for building a 3D model of a scene, define the tradespace of sensor designs capable of gathering this information, develop new sensors capable of dramatically increased measurement diversity, and validate all of the above via testing in the field.
This approach is potentially transformative because conventional infrared sensors fail to collect almost all available information from ambient thermal emissions. Invisible Headlights seeks to create superior sensors that capture more of this information via improved algorithms and increased measurement diversity.
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