SBIR-STTR Award

Affordable, Multi-wavelength Imager plus Light Detection and Ranging (LIDAR) for Autonomous Vehicles
Award last edited on: 1/16/2022

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,143,266
Award Phase
2
Solicitation Topic Code
EW
Principal Investigator
Shimon Maimon

Company Information

nBn Technologies LLC

136 Wilshire Road
Rochester, NY 14618
   (585) 355-5556
   N/A
   www.nbnir.com
Location: Single
Congr. District: 25
County: Monroe

Phase I

Contract Number: 1843757
Start Date: 2/1/2019    Completed: 1/31/2020
Phase I year
2019
Phase I Amount
$222,500
The broader impact/commercial potential of this project is to provide a low cost Lidar+Thermal camera to the autonomous car market that will eventually enable level 4 and level 5 autonomy. The proposed innovation incorporates both a Lidar and a thermal detector to locate objects but also classify them, as this is the most crucial aspect of autonomous vehicles. The dual polarity Lidar+Thermal photodetector solves a few major issues in the current Lidar industry. First, current Lidars have to use advanced algorithms to classify the objects, whereas a Lidar+Thermal detector can easily distinguish between animate and inanimate objects, while continuing to establish their location. This is done due to the drastic heat signature of animate objects. Second, the dual polarity detector is able to detect and locate hazards on the road such as snow or puddles, which is vital if autonomous vehicles are used in northern regions. In addition, the frame rate of the Flash Lidar+Thermal is up to 200 Frames per second, which will drastically reduce smearing effects and allow for driving at speeds of 70+ MPH. Lastly, the high thermal resolution of the camera will ensure operation in bad weather conditions including fog and rain.This Small Business Innovation Research (SBIR) Phase I project will provide a proof-of-concept of the dual polarity Lidar+Thermal detector. An array of 32x32 pixels will demonstrate that in one polarity, a thermal hot-mid-wave image and in the other polarity the pixels will operate in a time-of-flight mode for Flash Lidar operation. The pixel?s spectral response will range from 500nm up to 3.5?m in the Lidar mode. Characterization of the detector array will use the eye-safe 1550nm laser. The goal is to show a 200m Lidar operation with a high resolution of a few centimeters and thermal imaging with a thermal sensitivity of 4mK. The transition to Phase II will include an array size of 1000x500 with 10?m pixel pitch. The detector will be evaluated outdoors to demonstrate the detection of animate objects, snow and puddles and will be tested under fog conditions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Phase II

Contract Number: 2037859
Start Date: 8/1/2021    Completed: 7/31/2023
Phase II year
2021
Phase II Amount
$920,766
The broader impact/commercial potential of this Small Business Innovation Research Phase II project based on this SBIR sensor solution, with its high quality and low cost, will enable the advanced driver assistance systems (ADAS) industry to accelerate the progress to greater functionality of assisted driving, ultimately reaching full autonomy. The subject focal plane array (FPAS) chips may reduce the current US 36,560 annual vehicles deaths (the leading cause of death for those 1-54 years old) as well as reduce the 4.4 million injuries requiring medical attention and the $ 871 billion in damages and health costs. Additionally, improved assisted driving will enhance the mobility of seniors/disabled. Finally, the technology may reduce the societal carbon footprint by reducing congestion as a result of more fuel-efficient acceleration and braking. This Small Business Innovation Research Phase II project seeks to improve the current ADAS sensor suite to increase safety. Current ADAS systems require many different sensor technologies to be implemented simultaneously. These sensors are insufficient to achieve higher levels of autonomy limiting the vehicle’s used in poor conditions. The proposed sensor solution will function in low light and harsh weather conditions with high performance. The added sensor functionalities will reduce the processor bandwidth required to integrate and analyze sensor data and detect road hazards, increasing the accuracy of the system. Overall, this improvement in performance may increase the overall safety in ADAS vehicles. An evaluation system will be developed to characterize the sensor. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.