Survey on path and view planning for UAVs

Background In recent decades,unmanned aerial vehicles(UAVs)have developed rapidly and been widely applied in many domains,including photography,reconstruction,monitoring,and search and rescue.In such applications,one key issue is path and view planning,which tells UAVs exactly where to fly and how to search.Methods With specific consideration for three popular UAV applications(scene reconstruction,environment exploration,and aerial cinematography),we present a survey that should assist researchers in positioning and evaluating their works in the context of existing solutions.Results/Conclusions It should also help newcomers and practitioners in related fields quickly gain an overview of the vast literature.In addition to the current research status,we analyze and elaborate on advantages,disadvantages,and potential explorative trends for each application domain.

An area-based position and attitude estimation for unmanned aerial vehicle navigation

The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle(UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image(LNSEI) based objective function and simplex-simulated annealing(SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16(meter) for horizontal position, 9.72(meter) for altitude and 0.82(degree) for attitude.

Reliability analysis of multimodal scene matching based on correlation peaks

The navigation system plays a pivotal role in guiding aircraft along designated routes,ensuring precise and punctual arrival at destinations.The integration of scene matching with an inertial navigation system enhances the capability of providing a dependable guarantee for success-ful accomplishment of flight missions.Nonetheless,assuring reliability in scene matching encoun-ters significant challenges in areas characterized by repetitive or weak textures.To tackle these challenges,we propose a novel method to assess the reliability of scene matching based on the dis-tinctive characteristics of correlation peaks.The proposed method leverages the fact that the sim-ilarity of the optimal matching result is significantly higher than that of the surrounding area,and three novel indicators(e.g.,relative height,slope of a correlation peak,and ratio of a sub peak to the main peak)are determined to conjointly evaluate the reliability of scene matching.The pro-posed method entails matching a real-time image with a reference image to generate a correlation surface.A correlation peak is then obtained by extracting the portion of the correlation surface exhibiting a significant gradient.Additionally,the matching reliability is determined by considering the relative height,slope,and ratio of the peak collectively.Exhaustive experimental results with two sets of data demonstrate that the proposed method significantly outperforms traditional approaches in terms of precision,recall,and F1-score.These experiments also establish the efficacy of the proposed method in achieving reliable matching in challenging environments characterized by repetitive and weak textures.This enhancement holds the potential to significantly elevate scene-matching-based navigation.