Assessment of the Cutting Performance of a Robot Mower Using Custom Built Software

Abstract

Before the introduction of positioning technologies in agriculture practices such as global navigation satellite systems (GNSS), data collection and management were time-consuming and labor-intensive tasks. Today, due to the introduction of advanced technologies, precise information on the performance of agricultural machines, and smaller autonomous vehicles such as robot mowers, can be collected in a relatively short time. The aim of this work was to track the performance of a robot mower in various turfgrass areas of an equal number of square meters but with four different shapes by using real-time kinematic (RTK)-GNSS devices, and to easily extract data by a custom built software capable of calculating the distance travelled by the robot mower, the forward speed, the cutting area, and the number of intersections of the trajectories. These data were then analyzed in order to provide useful functioning information for manufacturers, entrepreneurs, and practitioners. The path planning of the robot mower was random and the turfgrass area for each of the four shapes was 135 m2 without obstacles. The distance travelled by the robot mower, the mean forward speed, and the intersections of the trajectories were affected by the interaction between the time of cutting and the shape of the turfgrass. For all the different shapes, the whole turfgrass area was completely cut after two hours of mowing. The cutting efficiency decreased by increasing the time, as a consequence of the increase in overlaps. After 75 minutes of cutting, the efficiency was about 35% in all the turfgrass areas shapes, thus indicating a high level of overlapping.

Autonomous Mowing and Turf-Type Bermudagrass as Innovations for An Environment-Friendly Floor Management of a Vineyard in Coastal Tuscany

“…The random operating pattern of the autonomous mower turned into frequent overlapping, leading to an overall higher working time to mow a given area compared to a systematic operating pattern. The autonomous mowers' efficiency was close to 37% for a surface with no obstacles [34], while in an area with many obstacles, such as the vineyard, the working efficiency of the machine results were even lower [25]. Despite a higher working time, during both years, the primary energy consumption of the innovative management system was lower compared to the primary energy consumption of the conventional management system.…”

Autonomous Mowers Working in Narrow Spaces: A Possible Future Application in Agriculture?

“…The percentage of area with obstacles mown in function of the time for the six autonomous mowers was studied separately for Site A and Site B. The extension package "drc" (Dose-Response Curve) of R [32] was used to fit the nonlinear regression model, plot the graphs, and estimate the parameters and the effective time values [29]. The non-linear function corresponded to a two-parameter asymptotic regression (Equation (1)):…”

“…One of the two Emlid Reach RTK devices was used as a base station and was installed outside the two working areas. The other Emlid Reach RTK device was used as a rover and was attached on each autonomous mower while it performed mowing [29]. The two Emlid Reach RTK devices recorded GNSS signals and calculated the distance between the base station and the rover by running the RTK algorithm.…”

Improved two-step analysis of germination data from complex experimental designs

“…However, for visualization of the fitted germination curves and their corresponding confidence bands, results from all model parameters are needed. This shortcoming has also been noted in other applications of the two-step meta-analytic approach beyond germination experiments (Martelloni et al, 2019).…”