Cascade Improved Visual Detection and Distance Estimation in Formation of Micro Unmanned Aerial Vehicles
According to the localization of UAVs in formation, this paper has proposed a visual based method using cascade classifiers of LBP and Haar-like features to realize UAVs’ detection and distance estimation. Since the phenomenon of overlapping in formation has an obvious influence on the performance of detection, this paper adopts the method of integrating two classifiers with different features (LBP and Haar) to improve the performance of detector. For the purpose of enhancing the precision of distance estimation, an optimized method is proposed based on the prediction of UAV’s attitude. The description of coordination is deducted to obtain accurately relative position from visual information. The results of test videos verify the performance of proposed method on the application of UAVs formation.
KeywordsLocalization UAVs formation Cascade
Foundation program: supported by Key Lab Fund of Shanxi province (XJZZ201704) and National Natural Fund (41419060201).
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