Quantitative estimation of rapeseed yield is important for precision crop management and sustainable agricultural development. Traditional manual measurements are inefficient and destructive, making them unsuitable for large-scale applications. This study proposes a canopy-volume estimation and yield-modeling framework based on unmanned aerial vehicle light detection and ranging (UAV-LiDAR) data combined with a HybridMC-Poisson reconstruction algorithm. At the early yellow ripening stage, 20 rapeseed plants were reconstructed in 3D, and field data from 60 quadrats were used to establish a regression relationship between plant volume and yield. The results indicate that the proposed method achieves stable volume reconstruction under complex canopy conditions and yields a volume–yield regression model. When applied at the field scale, the model produced predictions with a relative error of approximately 12% compared with observed yields, within an acceptable range for remote sensing–based yield estimation. These findings support the feasibility of UAV-LiDAR–based volumetric modeling for rapeseed yield estimation and help bridge the scale from individual plants to entire fields. The proposed method provides a reference for large-scale phenotypic data acquisition and field-level yield management.

In this research, a new method based on the equivalence of modal characteristics, differential flatness (DF), and active disturbance rejection control (ADRC) is proposed for the stabilization control of the long flexible arm (LFA). There are two major problems in the system of the LFA. The first problem is that the LFA is very prone to the multiple-mode coupling, while the control systems need as few sensors as possible. Another problem is that the structure of the LFA in practice is often complex and subject to various disturbances. Therefore, in this paper, the equivalent multirigid body dynamic model of a LFA is derived from the modal information of the equivalent rigid body model of the prototype. Then, the output values of the three tilt sensors are synthesized into an output based on the DF method. Finally, the effectiveness of the proposed method is verified through physical experiments. Compared with PID, the proposed method has shorter settling time. The LFA can be restored within 7 seconds under the ADRC, while it needs 90 seconds or more to calm down without the control.

The brake–release stability of electro-hydraulic thrusters (EHTs) significantly affects the safety of hydraulic braking systems, especially under low-temperature conditions with varying fluid viscosity. Most existing studies have focused on macroscopic braking characteristics, while the internal flow field variation and vortex evolution mechanism during the brake–release process remain insufficiently explored. In this work, transient CFD simulations are conducted to investigate vortex formation rules and flow field characteristics inside an EHT. Three typical vortex structures denoted as α, β, and γ are identified, and the independent and coupling influences of fluid dynamic viscosity and motor speed on vortex intensity and piston-bottom pressure are quantitatively analyzed. The results show that vortices α and β trigger flow disorder and additional hydraulic energy loss, while vortex γ optimizes flow uniformity and assists piston extension. Higher fluid viscosity exacerbates vortex development and pressure fluctuation, while increasing motor speed accelerates transient flow field evolution. This study clarifies the internal flow mechanism of EHT brake–release behavior and provides reliable parametric guidance for optimizing the low-temperature performance of electro-hydraulic braking systems.