Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework n...Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework named the Formation Interfered Fluid Dynamical System(FIFDS) with Moderate Evasive Maneuver Strategy(MEMS) is proposed in this study.First, the UAV formation collision avoidance problem including quantifiable performance indexes is formulated. Second, inspired by the phenomenon of fluids continuously flowing while bypassing objects, the FIFDS for multiple UAVs is presented, which contains a Parallel Streamline Tracking(PST) method for formation keeping and the traditional IFDS for collision avoidance. Third, to rationally balance flight safety and collision avoidance cost, MEMS is proposed to generate moderate evasive maneuvers that match up with collision risks. Comprehensively containing the time and distance safety information, the 3-D dynamic collision regions are modeled for collision prediction. Then, the moderate evasive maneuver principle is refined, which provides criterions of the maneuver amplitude and direction. On this basis, an analytical parameter mapping mechanism is designed to online optimize IFDS parameters. Finally, the performance of the proposed method is validated by comparative simulation results and real flight experiments using fixed-wing UAVs.展开更多
Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,...Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,frequency-domain methods rely on complex parameterization and spectral decomposition,which are sensitive to mesh topology and resolution and often introduce perceptible artifacts.Spatial-domain techniques,on the other hand,typically embed watermarks in global or randomly selected regions,leading to visible distortions and reduced robustness.To address the above limitations and protect model copyright without compromising the original aesthetic quality,we propose a deterministice PCA-synchronized 3Dmeshwatermarkingmethodwith fullerene-guided carrier selection.First,a deterministic principal component analysis(PCA)-based mesh synchronization algorithm is employed to align the models to a canonical pose.Next,a fullerene-inspired carrier selection strategy is employed to determine the watermark carriers,leveraging the structural characteristics of fullerene molecules to achieve a more rational and effective carrier selection.Finally,to balance the embedding strength and enhance visual quality,the watermark information is embedded using an APQIM(Adaptive Parity-Check Quantization Index Modulation)scheme.The experimental results show that our method can achieve high visual quality with scalable capacity and strong robustness compared with existing methods.The watermarking scheme can resist various attacks,including simplification,smoothing,Gaussian noise,translation,and rotation.展开更多
Nighttime navigation faces challenges from limited data and interference,especially when satellite signals are unavailable.Leveraging lunar polarized light,polarization navigation offers a promising solution for night...Nighttime navigation faces challenges from limited data and interference,especially when satellite signals are unavailable.Leveraging lunar polarized light,polarization navigation offers a promising solution for nighttime autonomous navigation.Current algorithms,however,are limited by the requirement for known horizontal attitudes,restricting applications.This study introduces an autonomous 3-D attitude determination method to overcome this limitation.Our approach utilizes the Angle of Polarization(AOP)at night to extract neutral points from the AOP pattern.This allows for the calculation of polarization meridian plane information for attitude determination.Subsequently,we present an optimized Polarization TRIAD(Pol-TRIAD)algorithm to acquire the 3-D attitude.The proposed method outperforms the existing approaches in outdoor experiments by achieving lower Root Mean Square Error(RMSE).For one baseline attitude,it improves pitch by 31.7%,roll by 21.7%,and yaw by 2.6%,while for the attitude with a larger tilt angle,the improvements are 64.4%,30.4%,and 9.1%,respectively.展开更多
基金supported in part by the National Natural Science Foundations of China(Nos.61175084,61673042 and 62203046)the China Postdoctoral Science Foundation(No.2022M713006).
文摘Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework named the Formation Interfered Fluid Dynamical System(FIFDS) with Moderate Evasive Maneuver Strategy(MEMS) is proposed in this study.First, the UAV formation collision avoidance problem including quantifiable performance indexes is formulated. Second, inspired by the phenomenon of fluids continuously flowing while bypassing objects, the FIFDS for multiple UAVs is presented, which contains a Parallel Streamline Tracking(PST) method for formation keeping and the traditional IFDS for collision avoidance. Third, to rationally balance flight safety and collision avoidance cost, MEMS is proposed to generate moderate evasive maneuvers that match up with collision risks. Comprehensively containing the time and distance safety information, the 3-D dynamic collision regions are modeled for collision prediction. Then, the moderate evasive maneuver principle is refined, which provides criterions of the maneuver amplitude and direction. On this basis, an analytical parameter mapping mechanism is designed to online optimize IFDS parameters. Finally, the performance of the proposed method is validated by comparative simulation results and real flight experiments using fixed-wing UAVs.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 62272331the Key Laboratory of Data Protection and Intelligent Management,Ministry of Education,Sichuan University and the Fundamental Research Funds for the Central Universities under Grant SCU2023D008.
文摘Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,frequency-domain methods rely on complex parameterization and spectral decomposition,which are sensitive to mesh topology and resolution and often introduce perceptible artifacts.Spatial-domain techniques,on the other hand,typically embed watermarks in global or randomly selected regions,leading to visible distortions and reduced robustness.To address the above limitations and protect model copyright without compromising the original aesthetic quality,we propose a deterministice PCA-synchronized 3Dmeshwatermarkingmethodwith fullerene-guided carrier selection.First,a deterministic principal component analysis(PCA)-based mesh synchronization algorithm is employed to align the models to a canonical pose.Next,a fullerene-inspired carrier selection strategy is employed to determine the watermark carriers,leveraging the structural characteristics of fullerene molecules to achieve a more rational and effective carrier selection.Finally,to balance the embedding strength and enhance visual quality,the watermark information is embedded using an APQIM(Adaptive Parity-Check Quantization Index Modulation)scheme.The experimental results show that our method can achieve high visual quality with scalable capacity and strong robustness compared with existing methods.The watermarking scheme can resist various attacks,including simplification,smoothing,Gaussian noise,translation,and rotation.
基金supported in part by the National Key Research and Development Program of China(Nos.2020YFA0711200,2022YFB4701301)in part by the Defense Industrial Technology Development Program,China(No.JCKY2021601B016)+1 种基金in part by the Fundamental Research Funds for the Central Universities,China(No.YWF-23-JC-07)in part by the National Natural Science Foundation of China(No.62425302)。
文摘Nighttime navigation faces challenges from limited data and interference,especially when satellite signals are unavailable.Leveraging lunar polarized light,polarization navigation offers a promising solution for nighttime autonomous navigation.Current algorithms,however,are limited by the requirement for known horizontal attitudes,restricting applications.This study introduces an autonomous 3-D attitude determination method to overcome this limitation.Our approach utilizes the Angle of Polarization(AOP)at night to extract neutral points from the AOP pattern.This allows for the calculation of polarization meridian plane information for attitude determination.Subsequently,we present an optimized Polarization TRIAD(Pol-TRIAD)algorithm to acquire the 3-D attitude.The proposed method outperforms the existing approaches in outdoor experiments by achieving lower Root Mean Square Error(RMSE).For one baseline attitude,it improves pitch by 31.7%,roll by 21.7%,and yaw by 2.6%,while for the attitude with a larger tilt angle,the improvements are 64.4%,30.4%,and 9.1%,respectively.
