Reciprocal Visibility for Guided Occlusion Removal With Drones
Sprache des Titels:
Englisch
Original Kurzfassung:
In this letter, a guidance strategy is proposed to optimize synthetic aperture sampling for occlusion removal with drones based on point-cloud representation of occluders. Prerecorded light detecting and ranging (LiDAR) scans are utilized to compute the visibility of fixed inspection regions on the ground that are intended for recurrent monitoring from the air. By utilizing Helmholtz reciprocity, the drone-collected LiDAR scans are used to computationally obtain a reciprocal visibility (RV) of potential drone positions in the air from points of interest on the ground. This visibility forms a basis for a novel navigation strategy. This strategy was shown to drive drones to optimal aerial monitoring positions, thus reducing occlusion and, consequently, the sampling time. Compared with previous unguided sampling, we achieve a 5%?20% higher visibility with 9?17 times less samples in our experiments.
Forschungs-