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
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 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.
