Introducing a Revolutionary New Sensor Modality: The World's only Monocular 3D Thermal Ranging™ Solution 

 

Owl's Patent Protected innovation provides  High-Definition 3D thermal Imaging with high precision ranging for safe autonomous operation in all weather, day or night.  

 

 

The Owl Difference

Thermal Ranging™ is a novel 3D sensor modality that uses proprietary AI deep learning and foveal optics to extract dense range maps from radiated heat signatures without illumination.

The most determinant variable in the autonomous market will always be safety. Manufacturers will continuously be tasked with determining which technology solutions most effectively mitigate liability risks and cost for safe operation.

Owl’s patented, 3D Thermal Ranger™ provides HD imaging and precision ranging representing a 150x improvement in resolution and cloud density of LiDAR. It operates day & night, in all weather, definitively classifies; pedestrians, cyclists, animals and vehicles, all the while calculating position, direction and speed to unlock safe autonomous and semi-autonomous operation.

Owl’s solutions deliver panoramic thermal imaging and dense range maps superior to active LiDAR or RADAR. Unlike cumbersome stereo approaches, a single 3D Thermal Ranger delivers range throughout the entire field of view (FOV) and is immune to vehicle vibration for reliable and robust mapping.

The Benefits of Monocular 3D Thermal Ranging

  • Safety - Pick the safest path based on the best information
  • Pedestrian Detection - Thermal sees all living objects even if they don’t move
  • Precision Ranging  - Delivers ultra-high density range maps
  • True 3D Velocity - Measures and reports angular velocity in three dimensions
  • “Always On” - Any condition, all weather & day/night
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A New Class of Imager - 3D Monocular Thermal Ranging

Owl Sees Everything

3D Location, Speed and Direction

High Frame Rate

Thermal Camera Exploded

AI CNN deep learning and multi-aperture optics

HD Thermal Video with Range Data

Object Classification

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