Agility Prime Researches Electronic Parachute Powered by Machine Learning - Aviation Today

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Kentucky-based Aviation Safety Resources is developing ballistic parachutes for use in aircraft ranging from 60 lbs to 12,000 lbs. The Air Force's Agility Prime program awarded a phase I small business technology transfer (STTR) research contract to Jump Aero and Caltech to create an electronic parachute powered by machine learning that would allow the pilot to recalibrate the flight controller in midair in the event of damage, the company announced on April 7. "The electronic parachute is the name for the concept of implementing an adaptive/machine-learned control routine that would be impractical to certify for the traditional controller for use only in an emergency recovery mode -- something that would be switched on by the pilot if there is reason to believe that the baseline flight controller is not properly controlling the aircraft (if, for example, the aircraft has been damaged in midair)," Carl Dietrich, founder and president of Jump Aero Incorporated, told Avionics International. This technology was previously difficult to certify because of the need for deterministic proof of safety within these complex systems. The research was sparked when the Federal Aviation Administration certified an autonomous landing function for use in emergency situations which created a path for the possible certification of electronic parachute technology, according to Jump Aero. The machine-learned neural network can be trained with non-linear behaviors that occur in an aircraft in the presence of substantial failures such those generated by a bird strike, Dietrich said.

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