Precise detection of canopy parameters is vital as it offers essential information for pest management in orchards. Among these parameters, leaf area density stands out as a key indicator of orchard canopies. A detection algorithm for leaf area density was proposed, and a leaf area density detection system for orchard canopies was designed based on the algorithm. By processing the point cloud data acquired by using LiDAR together with the algorithm, the total leaf area of the fitted leaves was calculated. Through an orthogonal regression experiment conducted on a laboratory-simulated canopy, this research established a mathematical calculation model ($R^2$ = 0.96) for determining the leaf area density of an orchard canopy. The leaf area density of an orchard canopy can be calculated using the total leaf area of the fitted leaves and an established mathematical model. To assess the accuracy of the detection system, both laboratory-simulated canopy experiments and real orchard canopy experiments were conducted. The results revealed that the absolute value of the mean relative error in the laboratory-simulated canopy experiments was 11.58%, and the absolute value of the mean relative error in the orchard canopy experiments was 16.75%. The research results have confirmed the feasibility of the LiDAR point cloud data processing algorithm. Furthermore, this algorithm can provide theoretical support for the subsequent development of intelligent plant protection equipment in orchards.

Aiming at the low mechanization level of orchards in hilly and mountainous areas of China and the mismatch between existing walking chassis and the soft soil and complex terrain of densely planted orchards, this paper systematically conducts simulation analysis and field verification on the trafficability of an electric tracked chassis, targeting the operation demands of sandy-loam densely planted orchards in hilly regions of Jiangsu Province. Theoretical calculation yields a maximum vertical obstacle-crossing height of 0.22 m, a maximum trench-crossing width of 0.63 m, and a maximum static sliding angle of 35° for the chassis. Based on the measured bulk density and angle of repose of orchard soil, the soil contact parameters are calibrated via the Box–Behnken response surface methodology, and a RecurDyn-EDEM bidirectional coupling simulation model is established. The dynamic responses of the chassis and soil disturbance patterns are analyzed under obstacle-crossing, trench-crossing, straight-line driving, slope-climbing and steering conditions. The results indicate that the geometric trafficability of the chassis satisfies the design requirements; low-speed operation and large-radius steering can effectively reduce soil disturbance, while a 30° soft soil slope exceeds the safe trafficability limit. Field tests show that the relative errors of driving wheel torque are all below 16%, and the average straight-line driving offset rate is 1.71%, verifying the reliability of the simulation model. This study provides technical support for the performance optimization of electric tracked chassis applied in densely planted orchards of hilly areas.