Safe and feasible path planning is crucial for achieving autonomous navigation of fixed-wing Unmanned Aerial Vehicles (UAVs) in complex environments. However, due to the high-speed flight and complex control requirements of fixed-wing UAVs, ensuring the feasibility and safety of planned paths in complex environments remains challenging. Researchers at Beihang University have developed a feasible path planning algorithm named Closed-loop Radial Ray A* (CL-RaA*). The core components of the CL-RaA* include an adaptive variable-step-size path search and a just-in-time expansion primitive. By integrating these two components and conducting safety checks on the trajectories to be expanded, the CL-RaA* can rapidly generate safe and feasible paths that satisfy the differential constraints of fixed-wing UAVs.

Modern flight control demands faster response, greater adaptability, and resilience against unknowns—challenges traditional control systems struggle to meet. Incremental Nonlinear Dynamic Inversion (INDI) has emerged as a compelling solution, shifting control logic away from models toward real-time measurements. In a sweeping two-part review, researchers chart the path of INDI from its mathematical roots to its growing role inapplications. With its modular structure and built-in robustness, INDI is no longer just an academic concept.

A servicing spacecraft equipped with a compliant flexible rod has emerged as an innovative solution for detumbling defunct satellites, but the contact-induced vibrations of the flexible rod and severe disturbance pose significant challenges to operational accuracy and safety. Despite the extensive research on vibration suppression and detumbling control for tumbling satellites, the combined application of nonlinear energy sink with active varying stiffness (NES-AVS) for flexible rod vibration suppression in servicing spacecraft has yet to be comprehensively studied, and addressing this research gap is crucial as existing methods struggle to achieve both vibration reduction and guaranteed control performance under contact-induced disturbance.

In the development of laser-driven color converters with simultaneously possessing excellent optical performance and superior heat dissipation, high-brightness laser lighting faces grave challenges. Herein, a reflective sandwich color converter of phosphor‐in‐glass film with sapphire and alumina (sapphire@PiGF@alumina, abbreviated as S@PiGF@A) is designed and prepared by a thermocompression bonding method. Benefiting from the high thermal conductivity and double-sided heat dissipation channels of alumina and sapphire, the S@PiGF@A color converter can withstand high laser power density and produce ultra-high luminescence. Consequently, the optimized S@PiGF@A converter yields white light with an ultrahigh luminous flux of 6749 lm at a laser power density saturation threshold of 47.70W/mm², which is 2.44 times that of traditional PiGF@alumina color converter (2522 lm@19.53 W/mm²). The findings provide valuable guidelines to design high quality PiGF color converter for high brightness laser-driven white lighting.

Zeolites have high ion exchange capacity and certain radiation resistance. However, their traditional synthesis methods have problems such as high temperature and pressure and difficult control of morphology. Moreover, powdered zeolites are prone to high pressure drop during dynamic adsorption, which limits their practical engineering applications. Therefore, developing spherical zeolites synthesis technology that combines high mechanical strength, excellent radiation resistance and efficient adsorption performance has become a core challenge in the field of radioactive pollution control.

As global airspace regulations evolve and drone usage surges, accurately tracking multiple UAVs in dynamic swarm formations has become a pressing challenge for aerial safety, urban air mobility, and counter-drone operations. A research team from Beijing Institute of Technology has developed a novel visual tracking framework that significantly improves the identification and tracking of visually similar drones with nonlinear motion in air-to-air scenarios. Their work marks a major step toward scalable, intelligent swarm drone monitoring in real-world applications.

With the increasing focus on the pursuit-evasion game, the guidance law capturability analysis has been widely studied recently to theoretically assess the performance of different guidance laws and reveal the impact of the physical constraints on capture zones. In a recent study, the capture zones of the continuous and pulsed guidance laws in the pursuit-evasion game are analytically discussed to provide deep insights into the capturability distinction between the continuous guidance law and the pulsed guidance law.

Moving mesh adaptation provides optimal resource allocation to computational fluid dynamics for the capture of different key physical features, i.e., high-resolution flow field solutions on low-resolution meshes. Although many moving mesh methods are available, they require artificial experience as well as computation of a posteriori information about the flow field, which poses a significant challenge for practical applications. Para2Mesh uses a double-diffusion framework to accomplish accurate flow field reconstruction through iterative denoising to provide flow field features as supervised information for fast and reliable mesh movement, thus enabling adaptive mesh prediction from design parameters.