Objective Current research on hedge trimming faces the challenge of developing a robotic system that can efficiently perform large-scale basic shape trimming while also handling complex shapes with precision. To address this issue, this study optimizes the mechanical structure and control system to design a new type of roadside hedge trimming robot, aiming to improve the quality of hedge trimming on both sides of road and reduce labor intensity.

Method A robotic system was constructed, consisting of a 6-degree-of-freedom SCARA robotic arm, a reciprocating shear cutter, and a small tracked chassis. The configuration of robotic arm was optimized. The control system employs a “PC + motion control card”, and C#-based upper computer software was developed for trajectory planning of robotic arm. Three trimming paths, i.e. linear, trapezoidal and arcuate, were planned and tested. A single-factor experiment was designed to evaluate trimming accuracy by analyzing shape error of hedges after trimming, with path interpolation interval and tool movement speed as variables. A weighted method was introduced to construct a comprehensive evaluation function, analyzing trimming performance under different parameter combinations. Trimming error and operation time were used as metrics for quantitative evaluation to explore the optimal combination of trajectory planning parameters.

Result Experiments verified robot’s trimming capability within a height range of 0.6 to 1.6 m and a lateral range of 0.5 to 1.2 m. Path interpolation interval and tool movement speed significantly affected trimming errors. The single-factor experiment results indicated that different parameter combinations influenced both trimming errors and operation time. Within set range, the straight-line hedge trimming performed best with an interpolation interval of 200 mm and a speed of 50 mm/s, the trapezoidal hedge trimming with an interval of 110 mm and a speed of 45 mm/s, and the arc-shaped hedge trimming with an interval of 108 mm and a speed of 45 mm/s, where the comprehensive evaluation function value was minimized, showing the best trimming accuracy and operational efficiency.

Conclusion Through the optimization of robotic arm structure and control system, this study successfully develops a new type of roadside hedge trimming robot, achieving the goals of both efficient and precise trimming. The results validate the robot’s trimming capabilities across different operational ranges and clarify the influence of trajectory planning parameters on trimming performance, providing technical support for hedge trimming automation. Future research will further optimize the robot’s performance to adapt to more complex real-world applications.