论文标题
Dronearchery：通过增强现实与触觉反馈和多重UAV碰撞的避免通过深度强化学习驱动的人类无人机互动
DroneARchery: Human-Drone Interaction through Augmented Reality with Haptic Feedback and Multi-UAV Collision Avoidance Driven by Deep Reinforcement Learning
论文作者
论文摘要
我们提出了一个新颖的概念，即由基于RL的蜂群行为驱动的增强现实（AR）人类无人机相互作用，以实现无人驾驶飞机的群体形成的直观和沉浸式的控制。美国开发的Dronearchery系统使用户可以快速部署一群无人机，从而产生模拟射箭的飞行路径。触觉界面LinkGlide将弓弦张力的触觉刺激带到前臂上，以提高瞄准的精度。释放的无人机群动态避免了彼此之间的碰撞，用户追随者的无人机以及基于深度强化学习的行为控制的外部障碍。 在这种情况下，使用人类对开发的概念进行了测试，在该场景中，用户从带有真实无人机的虚拟弓上射击以击中目标。人类操作员在AR中观察无人机的弹道轨迹，并通过触觉显示器实现了弓形张力的现实且高度可识别的体验。 实验结果表明，该系统通过应用AR技术并传达拉力的触觉反馈，将轨迹预测准确性提高了63.3％。在控制无人机时，Dronearchery用户强调了自然性（在5点李克特量表中的4.3分）和增加的信心（4.7中的4.7）。我们设计了触觉图案，以呈现触觉显示的四个滑动距离（张力）和三个施加力水平（刚度）。用户证明了通过触觉显示产生的触觉模式的能力，该触觉显示代表不同的弓弦张力（平均识别率为72.8％）和刚度（平均识别率为94.2％）。 该研究的新颖性是开发基于AR的无人机控制方法，该方法不需要操作员的特殊技能和培训。
We propose a novel concept of augmented reality (AR) human-drone interaction driven by RL-based swarm behavior to achieve intuitive and immersive control of a swarm formation of unmanned aerial vehicles. The DroneARchery system developed by us allows the user to quickly deploy a swarm of drones, generating flight paths simulating archery. The haptic interface LinkGlide delivers a tactile stimulus of the bowstring tension to the forearm to increase the precision of aiming. The swarm of released drones dynamically avoids collisions between each other, the drone following the user, and external obstacles with behavior control based on deep reinforcement learning. The developed concept was tested in the scenario with a human, where the user shoots from a virtual bow with a real drone to hit the target. The human operator observes the ballistic trajectory of the drone in an AR and achieves a realistic and highly recognizable experience of the bowstring tension through the haptic display. The experimental results revealed that the system improves trajectory prediction accuracy by 63.3% through applying AR technology and conveying haptic feedback of pulling force. DroneARchery users highlighted the naturalness (4.3 out of 5 point Likert scale) and increased confidence (4.7 out of 5) when controlling the drone. We have designed the tactile patterns to present four sliding distances (tension) and three applied force levels (stiffness) of the haptic display. Users demonstrated the ability to distinguish tactile patterns produced by the haptic display representing varying 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 for drone control that does not require special skills and training from the operator.
