DARPA introduces Invisible Headlights to utilize ambient thermal emissions that enable passive 3D vision at night

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.

To eliminate this vulnerability, DARPA announced the Invisible Headlights program. The fundamental research effort seeks to discover and quantify information contained in ambient thermal emissions in various environments, and creates new passive 3D sensors and algorithms to exploit that information.

The program includes three phases: Discovery that determines if thermal emissions contain sufficient information to enable autonomous driving at night or underground; Optimization that refines models, experimental designs, and ensure system feasibility for achieving 3D vision at both low speeds (<25 mph) and high speeds (>25 mph); and Advanced Prototypes that builds and tests passive demonstration systems that compete with active sensors.

“We’re aiming to make completely passive navigation in pitch dark conditions possible,” said Joe Altepeter, program manager in DARPA’s Defense Sciences Office. “In the depths of a cave or in the dark of a moonless, starless night with dense fog, current autonomous systems can’t make sense of the environment without radiating some signal—whether it’s a laser pulse, radar or visible light beam—all of which we want to avoid. If it involves emitting a signal, it’s not invisible for the sake of this program.”

Since everything—animate and inanimate—gives off some thermal energy, the goal is to discover what information can be captured from even an extremely small amount of thermal radiation and then develop novel algorithms and passive sensors to transform that information into a 3D scene for navigation.

“If we’re successful, the capability of Invisible Headlights could extend the environments and types of missions in which autonomous assets can operate – at night, underground, in the arctic, and in fog,” Altepeter said. “The fundamental understanding of what information is available in ambient thermal emissions could lead to advances in other areas, such as chemical sensing, multispectral vision systems, and other applications that exploit infrared light.”


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