- Detection range of 200 meters on objects with 10% reflectivity
- Clearly detecting objects out to 280 meters
- 1550nm laser
- Resolution of 300 vertical pixels, while simultaneously maintaining a frame rate of 10Hz
- Picture like resolution of 0.13 deg over 40 deg vertical FOV and 0.14 deg resolution over 100 deg horizontal FOV.
- Power consumption under 40W, said to be the most energy efficient system of any high- performance LiDAR currently available.
- Sensor head dimension 112 mm (h) x 145 mm (w) x 105 mm(d), with a roadmap to substantially reduce the future footprint and formfactor
- Single unit price is $35,000 for small quantities
PRNewswire: Frost & Sullivan recognizes Ouster OS-1:64 LiDAR with the 2018 Price/Performance Value Leadership Award for its enhanced capabilities, durability, and power efficiency, at affordable price points and compact size.
The OS-1:64 lidar sensor's simplified architecture and 7th-generation custom silicon design can measure 1.3M points per second using less than 17W of power, a feat that was previously difficult for high-performance lidar. Additionally, it has the range to detect objects up to a distance of 120m despite being 30 times smaller than competing solutions.
"Ouster's sensors are unique among high-resolution lidar sensors as they operate at the near-infrared 850nm wavelength. Its patented light filtering technology allows it to use the 2x signal found at 850nm, while avoiding the penalty of the 5x noise that is typical to this range," said Mariano Kimbara, senior industry analyst. "The 850nm wavelength has been shown to have lower atmospheric water vapor absorption and more consistent operation compared to other available lidar operating wavelengths. This translates to an operating wavelength that is not as absorbed by humid air or fog, and a heightened sensitivity of its low-cost silicon complementary metal-oxide semiconductor (CMOS) technology."
HAL archive paper "LIDAR sensor simulation in adverse weather condition for driving assistance development" by Mokrane Hadj-Bachir and Philippe de Souza gives some performance degradation data in different weather conditions: