Publications / Other Report

Biologically Inspired Interception on an Unmanned System

Chance, Frances S.; Little, Charles; McKenzie, Marcus M.; Dellana, Ryan A.; Small, Daniel E.; Gayle, Thomas R.; Novick, David K.

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.