Collision Avoidance of Two Autonomous Quadcopters
This work addresses safety in autonomous UAV operations, though it is incremental as it applies an existing game-theoretic method to a specific scenario.
The authors tackled the problem of mid-air collision avoidance for autonomous UAVs by developing a game-theoretic coordination mechanism based on fictitious play, resulting in successful implementation and collision avoidance in two quadcopters flying in opposite directions.
Traffic collision avoidance systems (TCAS) are used in order to avoid incidences of mid-air collisions between aircraft. We present a game-theoretic approach of a TCAS designed for autonomous unmanned aerial vehicles (UAVs). A variant of the canonical example of game-theoretic learning, fictitious play, is used as a coordination mechanism between the UAVs, that should choose between the alternative altitudes to fly and avoid collision. We present the implementation results of the proposed coordination mechanism in two quad-copters flying in opposite directions.