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We propose a novel concept of augmented reality (AR) human-drone interactiondriven by RL-based swarm behavior to achieve intuitive and immersive control ofa swarm formation of unmanned aerial vehicles. The DroneARchery systemdeveloped by us allows the user to quickly deploy a swarm of drones, generatingflight paths simulating archery. The haptic interface LinkGlide delivers atactile stimulus of the bowstring tension to the forearm to increase theprecision of aiming. The swarm of released drones dynamically avoids collisionsbetween each other, the drone following the user, and external obstacles withbehavior control based on deep reinforcement learning.  The developed concept was tested in the scenario with a human, where the usershoots from a virtual bow with a real drone to hit the target. The humanoperator observes the ballistic trajectory of the drone in an AR and achieves arealistic and highly recognizable experience of the bowstring tension throughthe haptic display.  The experimental results revealed that the system improves trajectoryprediction accuracy by 63.3% through applying AR technology and conveyinghaptic feedback of pulling force. DroneARchery users highlighted thenaturalness (4.3 out of 5 point Likert scale) and increased confidence (4.7 outof 5) when controlling the drone. We have designed the tactile patterns topresent four sliding distances (tension) and three applied force levels(stiffness) of the haptic display. Users demonstrated the ability todistinguish tactile patterns produced by the haptic display representingvarying bowstring tension(average recognition rate is of 72.8%) and stiffness(average recognition rate is of 94.2%).  The novelty of the research is the development of an AR-based approach fordrone control that does not require special skills and training from theoperator.

DroneARchery: Human-Drone Interaction through Augmented Reality with  Haptic Feedback and Multi-UAV Collision Avoidance Driven by Deep  Reinforcement Learning