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On-board Communication-based Relative Localization for Collision Avoidance in Micro Air Vehicle teams

机译:基于车载通信的碰撞相对定位   在微型飞行器团队中避免使用

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摘要

Micro Air Vehicles (MAVs) will unlock their true potential once they canoperate in groups. To this end, it is essential for them to estimate on-boardthe relative location of their neighbors. The challenge lies in limiting themass and processing burden needed to enable this. We developed a relativelocalization method that only requires the MAVs to communicate via theirwireless transceiver. Communication allows the exchange of on-board states(velocity, height, and orientation), while the signal-strength provides rangedata. These quantities are fused to provide a full relative location estimate.We used our method to tackle the problem of collision avoidance in tight areas.The system was tested with a team of AR.Drones flying in a 4mx4m area and withminiature drones of ~50g in a 2mx2m area. The MAVs were able to track theirrelative positions and fly several minutes without collisions. Ourimplementation used Bluetooth to communicate between the drones. This featuredsignificant noise and disturbances in signal-strength, which worsened as moredrones were added. Simulation analysis suggests that results can improve with amore suitable transceiver module.
机译:微型飞行器(MAV)可以分组运行,将释放其真正的潜力。为此,对他们来说,在船上估计邻居的相对位置至关重要。挑战在于限制实现这一目标所需的质量和处理负担。我们开发了一种相对定位方法,该方法仅要求MAV通过其无线收发器进行通信。通信允许交换板载状态(速度,高度和方向),而信号强度提供范围数据。这些量融合在一起以提供完整的相对位置估计值。我们使用我们的方法解决了在狭窄区域中避免碰撞的问题。该系统由一组AR无人机进行了测试。无人机在4mx4m的区域内飞行,微型无人机约50g 2mx2m的区域。 MAV能够跟踪其相对位置并飞行几分钟而不会发生碰撞。我们的实现使用蓝牙在无人机之间进行通信。这具有明显的噪声和信号强度干扰,随着添加了更多的无人机而加剧了。仿真分析表明,使用更合适的收发器模块可以改善结果。

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