Tracking Long-Distance Systematic Trajectories of Different Robot Mower Patterns with Enhanced Custom-Built Software

Abstract

Sustainable turfgrass management is essential for maintaining healthy and visually appealing green spaces. Autonomous mowers have emerged as an innovative solution, but the efficiency and quality of mowing operations depend on several factors. This study investigates the impact of mowing patterns and cutting heights on the performance of an autonomous mower through updated custom-built software. Three different mowing patterns (vertical, diagonal, and horizontal) and two cutting heights (3 cm and 6 cm) were analyzed to analyze mowing efficiency, coverage, and cutting uniformity. The vertical pattern emerged as the most effective, maximizing speed (0.52 m/s) and efficiency (0.77), while minimizing overlap (4.27 cm) and uncut areas (0.014 m2). In contrast, the horizontal and diagonal patterns showed lower efficiency (0.71 and 0.76) and less coverage percentage (97.05% and 96.71%) compared to the vertical pattern (98.57%). Cutting height influenced performance, with higher heights sometimes requiring adjustments to prevent inefficiencies. The interaction between the mowing pattern and cutting height was critical for optimizing both operational efficiency and cutting quality. These findings highlight the importance of selecting an appropriate mowing pattern and cutting height tailored to the specific operational goals.