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Robust Multi-Sensor Fusion for Micro Aerial Vehicle Navigation in GPS-Degraded/Denied Environments

机译:GPS降级/拒绝环境中的微空气车辆导航强大的多传感器融合

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State estimation for Micro Air Vehicles (MAVs) is challenging because sensing instrumentation carried on-board is severely limited by weight and power constraints. In addition, their use close to and inside structures and vegetation means that GPS signals can be degraded or all together absent. Here we present a navigation system suited for use on MAVs that seamlessly fuses any combination of GPS, visual odometry, inertial measurements, and/or barometric pressure. We focus on robustness against real-world conditions and evaluate performance in challenging field experiments. Results demonstrate that the proposed approach is effective at providing a consistent state estimate even during multiple sensor failures and can be used for mapping, planning, and control.
机译:微型空气车辆(MAVS)的状态估计是具有挑战性的,因为携带车载传感仪器受重量和功率约束的严重限制。此外,它们靠近和内部结构和植被的用途意味着GPS信号可以降低或全部使用。在这里,我们提出了一个适用于MAV的导航系统,其无缝地熔化GPS,视觉内径,惯性测量和/或气压的任何组合。我们专注于对实际条件的稳健性,并评估具有挑战性的现场实验中的性能。结果表明,即使在多个传感器故障期间,所提出的方法也有效地提供一致的状态估计,并且可用于映射,规划和控制。

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