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most citedMAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles

5 citations · 6 across the 3 of their papers we have counts for

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cs.RO2021★ 5 cited

MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles

Yu-Shun Hsiao, Zishen Wan, Tianyu Jia +6

Safety and resilience are critical for autonomous unmanned aerial vehicles (UAVs). We introduce MAVFI, the micro aerial vehicles (MAVs) resilience analysis methodology to assess th…