US-based automatic, dependent, surveillance-broadcast (ADS-B) unit provider uAvionix has partnered with Chinese drone maker DJI and Stanford University to develop disruptive sense and avoid technologies to help insure safe aircraft separation.
uAvionix stated that Stanford University Ph.D. candidate Eric Mueller has co-authored a paper titled ‘Multi-rotor Aircraft Collision Avoidance using Partially Observable Markov Decision Processes’, which explains how speed changes by agile multi-copters and small unmanned aerial systems (UAS) can be used in addition to horizontal and vertical manoeuvres to maintain safe operating distances between aircraft.
The Markov Decision Process (MDP) uses algorithms to model decision-making applications, including how an aircraft decides to manoeuvre to evade oncoming traffic.
uAvionix noted that it provided its miniature Ping ADS-B hardware for tests at Stanford University, in order to determine the effectiveness of the sense and avoid algorithms under development.
Designed to be a surveillance technology, ADS-B helps an aircraft in determining its position via satellite navigation and periodically broadcasts it, enabling it to be tracked.
The information can be received by air traffic control ground stations as a replacement for secondary radar, while it can also be received by other aircraft to provide situational awareness and allow self-separation.
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By GlobalDataMueller said: "Ping was the only system that provided a realistic way for us to validate our sense and avoid algorithms with live traffic for commercial aircraft separation assurance."
DJI supplied aircraft for testing for the endeavour.
