Welcome to USTC FLICAR Dataset!

— USTC FLICAR: A Multisensor Fusion Dataset of Lidar-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots

We present the USTC FLICAR Dataset, which is dedicated to the development of simultaneous localization and mapping and precise 3D reconstruction of the workspace for heavy-duty autonomous aerial work robots. In recent years, numerous public datasets have played significant roles in the advancement of autonomous cars and UAVs. However, these two platforms differ from aerial work robots: UAVs are limited in their payload capacity, while cars are restricted to two-dimensional movements. To fill this gap, we create the “Giraffe” mapping robot based on a bucket truck, which is equipped with a variety of well-calibrated and synchronized sensors: four 3D LiDARs, two stereo cameras, two monocular cameras, Inertial Measurement Units (IMUs), and a GNSS/INS system. A laser tracker is used to record the millimeter-level ground truth positions. We also make its ground twin, the “Okapi” mapping robot, to gather data for comparison. The proposed dataset extends the typical autonomous driving sensing suite to aerial scenes. Therefore, the dataset is named “FLICAR” to denote flying cars. We believe this dataset can also represent the flying car scenarios, specifically the takeoff and landing of VTOL (Vertical Takeoff and Landing) flying cars.

Are We Ready for Aerial Work Robots? Or Be Bolder, Flying Cars?

Some aerial work scenarios in our daily life:


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Acquisition System

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Sensors & Usage

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