BARRON ASSOCIATES, INC. — National Aeronautics and Space Administration SBIR Phase I: A2

BARRON ASSOCIATES, INC. — SBIR Phase I award from National Aeronautics and Space Administration.

Amount
$131,385
Agency
National Aeronautics and Space Administration
Program / Phase
SBIR · Phase I
Topic
A2
Solicitation
SBIR_21_P1
NAICS
Place of performance
VA
Period
2021-05-07 → 2021-11-19

Description

The air transportation system is on the verge of drastic change.nbsp; Enabled by technological advances in areas including electric propulsion, and machine learning, emerging vehicles have the potential to drastically lower transportation costs.nbsp; Vertical takeoff and landing (VTOL) capabilities enabled by distributed electric propulsion (DEP) are expanding operational flexibility, and will allow vehicles to takeoff and land in nearly any area, including dense urban areas.nbsp; With autonomous and highly augmented operations on the rise, companies such as Uber and Amazon envision Advanced Air Mobility (AAM) Operations including both high-density Urban Air Mobility (UAM) and rural area operations.nbsp; These AAM operations will provide rapid ldquo;air-taxirdquo; and cargo services.nbsp; Future vehicles and operations will give rise to a wide variety of new safety issues as well as require new approaches to address long-standing issues that have, to date, been handled by well-trained human pilots. Among the most important is the ability to safely conduct an emergency landing. The proposed autonomous LiDAR-supported Emergency Landing System for AAM (LELSA) emulates the perception, cognition, and decision making of expert operators to provide an onboard capability for crewed and uncrewed aircraft to accomplish the complex emergency (precautionary or forced) landing task autonomously.nbsp; This LiDAR (Light Detection and Ranging) enhanced autonomous emergency landing system leverages both existing data and data acquired through in-flight perception (LiDAR) to: (1) locate potential emergency landing sites; (2) continuously generate precautionary and forced landing plans that maximize both the quality of LiDAR-based site assessment updates and the likelihood of a safe landing; (3) continuously update its on-board site assessments based on incoming LiDAR data (newly acquired knowledge); and (4) provide emergency flight plan information to the existing on-board flight computer.