XPONENTIAL – uAvionix, DJI, And Stanford University Partner In Safe Aircraft Separation

In an era of increasing incidences of drone/airliner “near misses,” 3 organizations are working together on disruptive sense and avoid technologies to help insure safe aircraft separation.

PALO ALTO, Calif., April 27, 2016 /PRNewswire/ — In an era of increasing incidences of drone/airliner “near misses,” 3 organizations are working together on disruptive sense and avoid technologies to help insure safe aircraft separation.

Eric Mueller works at the NASA Ames Research Center and is a Ph.D. candidate at Stanford University. He co-authored a paper with his professor, Mykel Kochenderfer at Stanford, titled “Multi-rotor Aircraft Collision Avoidance using Partially Observable Markov Decision Processes.” The paper describes how speed changes by agile multi-copters and small unmanned aerial systems (UAS) can be used in addition to horizontal and vertical maneuvers to maintain safe operating distances between aircraft.

The Markov Decision Process (MDP) uses algorithms to model decision making, such as how an aircraft decides to maneuver to avoid oncoming traffic. MDP is applied in situations where some variables are possibly random (such as how another aircraft may decide to maneuver) and others are under the control of the decision maker (such as an aircraft’s autopilot.)

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