The landscape industry is facing increasing labor shortages and rising operational costs, leading to a growing interest in automation. Autonomous mowing technology has the potential to address these challenges by reducing labor dependency and increasing efficiency. However, there is limited research evaluating the return on investment (ROI) and performance of these mowers in real-world conditions. One of the primary concerns for landscape professionals is whether autonomous mowers can operate effectively across various terrains and obstacle-heavy environments while maintaining efficiency and safety standards. This study assessed the performance of autonomous and manual mowers by measuring mowing time, energy consumption, and adaptability across different landscapes. Two mower types were tested: a manual battery-powered mower and an autonomous gas-powered mower. Testing was conducted on two landscape designs—a simple square plot and a complex plot with obstacles—to analyze variations in efficiency, along with two turf types. There was no significant difference in either mower’s performance on bermuda or ryegrass. Preliminary results indicate that manual mowers perform significantly faster than autonomous mowers, and the autonomous mowing time increases significantly in complex landscapes. The energy consumption of the gas autonomous mower is higher than that of manual battery-powered mowers. Factors such as sensor reliability and obstacle detection remain areas of concern. The collected data provides insight into the operational efficiency of autonomous mowers and their potential impact on the landscape industry. Future research will focus on calculating ROI values by incorporating cost analysis and industry data, as well as investigating safety protocols related to obstacle detection and avoidance to enhance autonomous mowing technology for commercial use.
