LoRa Backscatter Assisted State Estimator for Micro Aerial Vehicles with Online Initialization

The advances in agile micro aerial vehicles (MAVs) have shown great potential replacing humans for labor-intensive or dangerous indoor investigation, such as warehouse management and fire rescue. However, the design of a state estimation system that enables autonomous flight poses fundamental challenges dim smoky environments. Current dominated computer-vision based solutions only work well-lighted texture-rich This paper addresses challenge by proposing Marvel, an RF backscatter-based with online initialization calibration. Marvel is nonintrusive to commercial MAVs attaching backscatter tags their landing gears without internal hardware modifications, works plug-and-play fashion automatic module. enabled three new designs, pose sensing module, calibration backscatter-inertial super-accuracy algorithm. We demonstrate our programming MAV autonomously fly different trajectories. results show supports navigation within range 50 m through concrete walls, accuracy 34 cm localization 4.99 orientation estimation. further comparing perfect initial parameter measurements from burdensome manual operations.