# Monitoring Autonomous Mowers Operative Parameters on Low-Maintenance Warm-Season Turfgrass
## 1 Introduction  
A challenge of managing turfgrass is to maintain high quality for the intended use [1]. Both turfgrass visual and functional quality are strongly dependent on the management practices and intensities adopted. If properly conducted, moving can significantly improve turf quality, and its effect is defined by three main components: height of cut, frequency of cut, and mower type [2]. Plants response to the biomass removal resulting from moving is a key aspect of high-quality turfgrass maintenance [3]. However, achieving adequate turfgrass quality performance according to different contexts is dependent on the turf species, cultivars, and moving technology [4]. Technology advances achieved in automation and precision agriculture techniques for turf management are becoming more popular and user-friendly. Robot mowers demonstrated to provide many additional advantages, such as saving human labor, reducing local pollutants, and avoiding potential injuries and exposure to dust from moving [5, 6]. Robot mowers conduct repetitive operations with minimal human interaction [7]. The repetitive activity of autonomous mowers is critical in maintaining greenspaces, which must be moved for extended periods of time toprovide a continuous covering of the areas. The complicated shape and pattern of urban and ornamental areas may increase working time, especially for the autonomous mower with a random pattern, resulting in a non-homogeneous cut and increased energy consumption [8]. An additional issue in greenspace maintenance is the presence of buildings and trees, which can lead to an increase in working time due to GPS signal loss and the associated decreased positioning accuracy [9]. Studies have been conducted to understand how autonomous mowers (AMs) affect turfgrass management and different establishments, turf architecture, and competition with weeds. In general, autonomous mowers constant activity has been shown to improve turf quality by enhancing turf density, decreasing weed incidence, and improving leaf texture (in general smaller and finer) [10]. In addition, continuous mechanical stress and trampling damage attributed to autonomous mowers are challenging factors for turfgrass quality [11]. In this regard, [PERSON] et al. [12] and [PERSON] et al. [11] analyzed fundamental parameters related to the random trajectories. The Real Time Kinematic navigation system was very helpful to better understand the effective impact of autonomous mowers trampling damages and soil compaction. The data obtained were analyzed with the custom-built software \"Robot mower tracking data calculator\" version 1.7.0.0. (Qprel s.r.l., Pistoia, Italy) to calculate the autonomous mower overlapping, trajectories, number of passages, percentage of area moved, and correlated turfgrass stress and soil compaction [13]. According to [PERSON] et al. [14], trampling damages deriving from mechanical stress and soil compaction are key aspects of turfgrass maintenance. Soil compaction is recognized as one of the major traffic problems on turfgrass, which could affect the visual parameters of turf quality. It also compromises the soil assessment and its pores space composition with a series of problems connected. The degree of soil compaction created by vehicular traffic depends on speed, the surface contact area with the soil, and the weight [15]. Poor management practices, disease, and extreme environmental conditions could facilitate weed encroachment, thus reducing turf quality. A more environmentally friendly strategy for turfgrass management should be implemented, considering the green area itself and species biology and ecology in order to optimize inputs and operations effects [1; 2]. [PERSON] et al. [16] demonstrated how accurate planning of greenspaces and a suitable maintenance operations schedule lead to time, energy, and money savings, and in some cases, improved turfgrass aesthetic and functional quality.