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Low-SWaP and Low-Cost Autonomous Landing Area Confirmation Scan (AutoLACS) Tool

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC23PB364
Agency Tracking Number: 231374
Amount: $156,493.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A2
Solicitation Number: SBIR_23_P1
Timeline
Solicitation Year: 2023
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-07-18
Award End Date (Contract End Date): 2024-02-02
Small Business Information
1410 Sachem Place, Suite 202
Charlottesville, VA 22901-2496
United States
DUNS: 120839477
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Nathan Richards
 (434) 973-1215
 barron@bainet.com
Business Contact
 Mary Crawford
Title: General Manager
Phone: (434) 973-1215
Email: crawford@bainet.com
Research Institution
N/A
Abstract

The air transportation system is on the verge of drastic change.nbsp; Enabled by technological advances in areas including electric propulsion, computational capabilities, and machine learning, emerging vehicles have the potential to drastically lower transportation costs.nbsp; Vertical takeoff and landing (VTOL) capabilities 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, the industry envisions near-future 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;, cargo, and emergency 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 previously been handled by well-trained human pilots. Among the most important is the ability to autonomously confirm the suitability of a planned landing area prior to landing. The proposed autonomous Landing Area Confirmation Scan (AutoLACS) emulates the perception, cognition, and decision making of expert operators to provide an autonomous onboard capability to confirm the suitability of an intended landing area (runway, helipad, vertiport, off-field, etc.) in support of safe integration of UAS and AAM/UAM into the National Airspace System (NAS).nbsp; The AutoLACS tool provides a low-cost and low-SWaP approach to identifying hazards on an intended landing surface.nbsp; The key AutoLACS innovation is the use of low-cost and low-SWaP digital camera imagery (topographic photogrammetry), together with publicly available LiDAR data, to rapidly confirm the suitability of an intended landing area and to use this information to inform a multi-objective go-around/rejected-landing decision.

* Information listed above is at the time of submission. *

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