Cutting Edge Technologies: Assessing ROI and Safety of Autonomous Mowers

Abstract

Landscape services in the United States is an expansive industry, producing upwards of $221.89B in economic output over more than 100,000 landscape companies (Hall et al., 2020). Despite this economic strength, the industry faces growing operational challenges, particularly related to labor shortages. Autonomous mowers offer a variety of potential benefits to the landscape industry, such as reduced mowing times, reallocation of labor, and higher operating efficiencies. In this experiment, four different types of zero-turn, commercial mowers were tested in this experiment: battery-powered manual, gas-powered manual, battery-powered autonomous, and gas-powered autonomous. Testing was conducted on two landscape designs—a simple square plot with no obstacles and a complex plot with obstacles—to analyze variations in efficiency. Turfgrass species had no statistically significant effect on energy consumption for either mower type. Across tests, 1.23 mL of gasoline corresponded to 1 Wh of battery energy. Autonomous mowers took much longer to complete the free plots compared to the manual mowers, increasing average time to cut to 33.7 minutes per acre. These data suggest that the most suitable context for these mowers is large, unobstructed turfgrass areas, such as sports fields, municipal parks, and large campus grounds, where path complexity and obstacle density are minimal. However, as autonomous mowing equipment continues gain popularity, many consumers have concerns and hesitations regarding the safety of autonomous mowers. Two different types of technologies were tested in this experiment: one autonomous mower equipped with 4 stereo RGB cameras, and one autonomous mower equipped with 5 radars. Both types of detection technologies were evaluated with different obstacle sizes, colors, and approach angles. Overall, the Wright mower equipped with stereo RGB cameras was more effective at detecting all obstacles, resulting in a 93.8% probability rate, compared to the Bobcat mower equipped with a radar system, which had a probability of 61.8%. These data suggest that large platform autonomous mowers cannot be unsupervised in an area where adult and child obstacles may be present while the mower is working.