Low-altitude UAV obstacle detection method based on position constraint and attention

Abstract

UAVs are widely used in low-altitude fields for tasks such as power inspection, search and rescue, and reconnaissance. Pre-detection of obstacles during flight is a safety guarantee for completing the given tasks. In order to meet the requirements of obstacle detection accuracy and position regression accuracy when UAVs are flying at low altitudes, a low-altitude UAV obstacle detection method based on position constraint and attention improvement is proposed. Firstly, the shortcomings of the position regression loss function are analyzed, and based on this, a loss function of separating scale loss and integrating direction constraint is proposed to optimize the regression process; secondly, the attention mechanism CBAM is improved, and a dual attention mechanism is proposed to strengthen
the feature suppression interference and improve the detection performance. The experimental results show that the improved algorithm has improved mAP 2.28%and mAP@0.5:0.95 2.7%, and has shown better low-altitude obstacle detection performance in both detection accuracy and position regression accuracy.