Integration of Semantic Segmentation and Fuzzy Reasoning for Unmanned Aerial Vehicle Emergency Landing Site Selection Algorithm
With the expansion of the application fields of drones from recreational photography to logistics,military oper-ations,and disaster response,the demand for the autonomy and intelligence of drones has increased significantly.Addressing the challenge of ensuring autonomous safe landings in complex and unpredictable emergency landing zones,a novel landing site selection algorithm,named STDC-LSSNet(semantic target detection and control for landing site selection net),is proposed by integrating a real-time semantic segmentation network with fuzzy reasoning.Firstly,to address the issue of potential danger factors having a small proportion in aerial images and being prone to missegmentation,a small target feature capture module(STFCM)is introduced.This module calculates the similarity of features at different scales and assigns weights to enhance the representation of small target features effectively.Secondly,considering the risk associ-ated with the confusion between safe and hazardous areas during drone landing due to unclear boundaries,a boundary feature fusion module(BFFM)is introduced.This module combines the boundary information obtained from Laplacian convolution in shallow networks with the semantic information from deep networks,incorporating an attention mechanism to reinforce the representation of boundary region features.Finally,fuzzy reasoning is performed on the segmented images to accurately identify the emergency landing location.The proposed method is extensively evaluated on public datasets,Semantic Drone and AeroScapes,and compared with state-of-the-art algorithms.The results show a significant improve-ment in mean intersection over union(mIoU)by 1.72 percentage points and 3.89 percentage points.The real-time seg-mentation speed reaches 210 FPS,and the selection speed achieves 58.62 ms,demonstrating the effectiveness of the proposed approach in enabling drones to autonomously select emergency landing sites in complex scenarios.
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