| Abstract | This paper presents an aeronautical-grade payload unit designed for real-time execution of visual-inertial-LiDAR odometry and mapping (VILOAM) algorithms. The payload offers platform interchangeability between full-scale aircraft (e.g., Bell 412 helicopter), small-scale drones (e.g., DJI M600), and ground platforms. The use of small-scale drones renders a convenient option for the research and development of VILOAM algorithms due to the reduced resource demand and simplified pilot training, while full-scale aircraft experiments provide important operationally relevant datasets to test navigation algorithm performance for field deployment. The payload unit consists of two monocular cameras, an inertial measurement unit (IMU), a light detection and ranging (LiDAR) sensor, and a real-time kinematic (RTK) enabled global navigation satellite system (GNSS) receiver. A portable GPU interfaces with these sensors to capture hardware time-synchronized sensing data and perform real-time VILOAM, including support for AI modules for obstacle detection, emergency landing zone detection that typically occurs in field robotic applications such as last-mile goods delivery, surveillance and search and rescue flights. Field validation results for the payload unit are provided by running the developed VILOAM algorithm, as well as state-of-the-art VILOAM algorithms, and evaluating their performance in real-time localization and mapping on both platforms. |
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