Biologically Inspired Interception on an Unmanned System

Technical Report · 01 October 2021

DOI:https://doi.org/10.2172/1827493· OSTI ID:1827493

Novick, David ^[1]; Chance, Frances ^[1]; Little, Charles ^[1]; McKenzie, Marcus ^[1]; Dellana, Ryan ^[1]; Small, Daniel ^[1]; Gayle, Thomas ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Borrowing from nature, neural-inspired interception algorithms were implemented onboard a vehicle. To maximize success, work was conducted in parallel within a simulated environment and on physical hardware. The intercept vehicle used only optical imaging to detect and track the target. A successful outcome is the proof-of-concept demonstration of a neural-inspired algorithm autonomously guiding a vehicle to intercept a moving target. This work tried to establish the key parameters for the intercept algorithm (sensors and vehicle) and expand the knowledge and capabilities of implementing neural-inspired algorithms in simulation and on hardware.

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: NA0003525
• OSTI ID: 1827493
• Report Number(s): SAND2021-13549R; 701159
• Country of Publication: United States
• Language: English

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