Autonomous Mower Research Articles

Analysis of Football Pitch Performances Based on Different Cutting Systems: From Visual Evaluation to YOLOv8

The quality of sports facilities, especially football pitches, has gained significant attention due to the growing importance of sports globally. This study examines the effect of two different cutting systems, a traditional ride-on mower and an autonomous mower, on the quality and functional parameters of a municipal football field. The analysis includes visual assessments, measurements of grass height, and evaluations of surface hardness, comparing the performance of the two cutting systems. Additionally, studies of turfgrass composition and machine learning techniques, particularly with YOLOv8s and YOLOv8n, are conducted to test the capability of assessing weed and turfgrass species distribution. The results indicate significant differences in grass color based on the position (5.36 in the corners and 3.69 in the central area) and surface hardness between areas managed with a traditional ride-on mower (15.25 Gmax) and an autonomous mower (10.15 Gmax) in the central region. Higher height values are recorded in the area managed with the ride-on mower (2.94 cm) than with the autonomous mower (2.61 cm). Weed presence varies significantly between the two cutting systems, with the autonomous mower demonstrating higher weed coverage in the corners (17.5%). Higher overall performance metrics were obtained through YOLOv8s. This study underscores the importance of innovative management practices and monitoring techniques in optimizing the quality and playability of a football field while minimizing environmental impact and management efforts.

Performance of Different Cool-Season Species and Cultivars Overseeded on Bermudagrass and Managed with Autonomous Mower

With global warming, the cultivation area of bermudagrass is moving northwards in the Mediterranean area despite its winter dormancy and loss of green color. The most common solution is overseeding with perennial ryegrass, which can be complicated to remove in spring. DLF breeders have released a new cultivar of annual ryegrass that is stress tolerant and easy to transition in spring. A trial was carried out on a sod farm in Pisa, Italy. Twenty-nine varieties of cool-season grasses, encompassing both forage and turf species, were overseeded on a hybrid bermudagrass variety ‘Tifway’ (Cynodon dactylon x transvaalensis). The aim of this trial was to compare the overseeding potential of various cool-season turfgrass species and cultivars and to identify which ones perform best in terms of cleanness of cut when overseeded on hybrid bermudagrass in autumn and maintained at a mowing height of 25 mm. Moreover, the following parameters were also assessed: actual turf height (cm); cumulated height (cm); turf visual color and quality (1–9 scale); and visual ground cover (%). Plots were managed with an autonomous mower, which adopted a daily mowing frequency and was set to work with systematic trajectories. The results showed differences between cultivars, and the annual ryegrass showed the best spring transition (scoring a mean value of 96% green cover in July 2023) compared to the other entries. The best result of CoC was measured for rough-stalked meadow grass ‘Sabrena 1’ and tall fescue ‘Turfway’ with 0.9 mm.

Assessment of the Effects of Autonomous Mowers on Plant Biodiversity in Urban Lawns

Gaining information on the impact of lawn management with autonomous mowers on the floristic composition is crucial to improve their plant biodiversity. In this study, an autonomous mower with a reduced mowing frequency and a more sporadic mowing management system with a ride-on rotary mower were compared in terms of the effect on three dicotyledonous species (Phyla nodiflora, Lotus corniculatus and Sulla coronaria) transplanted onto stands of Bermuda and Manila grass. Regardless of the management system, P. nodiflora achieved the best results in terms of survival for both lawns (74.92 and 58.57% in Manila and Bermuda grass, respectively). In Bermuda grass, a higher percentage of surviving individuals was observed for the ordinary mower management system (42.59%), rather than with the autonomous mower (9.10%), while no differences emerged on Manila grass. On both Manila and Bermuda grass, a higher average percentage of coverage for single individual was observed for the ordinary mower management system (1.60 and 0.37%, respectively) compared to the autonomous mower system (0.55 and 0.08%, respectively). P. nodiflora had a higher percentage of individuals with flowers with the ordinary management system rather than with autonomous mower system both on Manila (60.73% and 33.90%, respectively) and Bermuda grass (48.66 and 3.32%, respectively). Despite a lower impact on the planted species being observed for the ordinary mower management system, encouraging results were obtained with the autonomous mower, for instance regarding the percentage of surviving individuals for P. nodiflora (33.95%) and L. corniculatus (22.08%) on Bermuda grass and the percentage of individuals with flowers for the same two species (33.90 and 13.59%, respectively) on Manila grass. Furthermore, the autonomous mower management system’s primary energy consumption over the year was lower compared to that of the ordinary system both on Manila (200.4 and 614.97 kWh ha−1 year−1, respectively) and Bermuda grass (177.82 and 510.99 kWh ha−1 year−1, respectively).

Autonomous Compared with Conventional Mower Use on St. Augustinegrass Lawn Quality

Autonomous (i.e., robotic) mowers have recently garnered interest with the public and within the turfgrass industry. However, limited research has been conducted on their use for mowing warm-season turfgrasses. An experiment was conducted at the University of Florida’s West Florida Research and Education Center (Jay, FL, USA) to investigate the performance of an autonomous mower using a lower than recommended height-of-cut on St. Augustinegrass (Stenotaphrum secundatum). Treatments included an autonomous mower with a height-of-cut of 2.5 inches set to mow daily and a conventional mulching mower with weekly mowing at recommended height-of-cut of 3.5 inches. Data collection included weekly digital images that were subjected to digital image analysis to determine overall turfgrass quality, percent green cover, and uniformity. The autonomous mower resulted in greater overall turfgrass quality from January to March and in November, and greater green cover from November to April compared with conventional mowing. Additionally, the autonomous mower produced greater turfgrass uniformity than conventional mowing. Results indicate that autonomous mowers can be successfully used to maintain St. Augustinegrass at a lower than recommended height-of-cut.

Monitoring Autonomous Mowers Operative Parameters on Low-Maintenance Warm-Season Turfgrass

Robotic solutions and technological advances for turf management demonstrated excellent results in terms of quality, energy, and time consumption. Two battery-powered autonomous mowers (2 WD and 4 WD) with random patterns were evaluated according to different trampling levels (control, low, medium, high) on a typical warm season turfgrass at the DAFE, University of Pisa, Italy. Data on the percentage of area mowed, the distance traveled, the number of passages, and the number of intersections were collected through RTK devices and processed by a custom-built software (1.8.0.0). The main quality parameters of the turfgrass were also analyzed by visual and instrumental assessments. Soil penetration resistance was measured through a digital penetrometer. The efficiency significantly decreased as the trampling level increased (from 0.29 to 0.11). The over-trampled areas were mainly detected by the edges (on average for the medium level: 18 passages for the edges vs. 14 in the central area). The trampling activity caused a reduction in turf height (from about 2.2 cm to about 1.5 cm). The energy consumption was low and varied from 0.0047 to 0.048 kWh per cutting session. Results from this trial demonstrated suitable quality for a residential turf of the Mediterranean area (NDVI values from 0.5 to 0.6), despite the over-trampling activity. Soil penetration data were low due to the reduced weight of the machines, but slightly higher for the 4 WD model (at 5 cm of depth, about 802 kPa vs. 670 kPa).

Continuous Mowing for Erigeron canadensis L. Control in Vineyards

Erigeron canadensis L. directly competes with vines for nutrients, light, and water, and its management represents a challenge, especially under a vineyard trellis. Conventional weed control in the under-trellis area is achieved by cultivation or multiple herbicides applications, thus leading to relevant environmental issues. For this reason, several eco-friendly or nature-based weed control strategies such as the use of cover crops (CC) that become more relevant in last years. A two-year trial was conducted on a vineyard aimed at evaluating the effect of CC (sown both inter-rows and under-trellis) managed with an autonomous mower (AM) on E. canadensis under trellis control. The combination of CC and AM provided an E. canadensis reduction between 61 and 84% compared to conventional management. The AM work when managing a spontaneous cover provided a density reduction of 26%. Moreover, an analysis of the trampling effect of the AM on the vineyard floor and E. canadensis density was conducted.

Localization Method Using Camera and LiDAR and its Application to Autonomous Mowing in Orchards

This paper presents a localization method using deep learning and light detection and ranging (LiDAR) for unmanned ground vehicle (UGV) in field environment. We develop a sensor fusion algorithm that UGV recognizes natural objects from RGB camera using deep learning and measures the distance to the recognized objects with LiDAR. UGV calculates its position relative to the objects, creates a reference path, and then executes path following control. The method is applied to autonomous mowing operation in orchard. A mower is tracked by UGV. UGV needs to run along a tree row keeping an appropriate distance from tree trunks, by which the mowing arm of the tracked mower properly touches the trunks. Field experiments are conducted in pear and apple orchards. UGV localizes self position relative to trees and performs autonomous mowing successfully. The results show that the presented method is effective.

Trampling Analysis of Autonomous Mowers: Implications on Garden Designs

Several trials have been carried out by various authors concerning autonomous mowers, which are battery-powered machines. The effects of these machines on turfgrass quality and energy consumption have been thoroughly investigated. However, there are still some aspects that have not been studied. Among these, random trajectory overlapping is one of the most important. To investigate these aspects, two RTK-GPS devices along with the custom-built software used for previous trials has been upgraded in order to precisely calculate how many times the mower drives over the same spot using random trajectories. This parameter, the number of passages in the same position, was hypothesized to explain the autonomous mower’s overlapping and trampling action. The trial has been carried out testing a commercial autonomous mower on three areas with different levels of complexity to assess its performances. The following variables were examined: the percentage of mowed area, the distance travelled, the number of intersections, the number of passages, and the autonomous mower’s work efficiency. The average percentage of area mown (average value for the three areas) was 54.64% after one hour and 80.15% after two hours of work. Percentage of area mown was 15% higher for the area with no obstacles after two hours of work. The number of passages was slightly different among the three garden designs. The garden with no obstacles obtained the highest number of passages with an average of 37 passages. The highest working efficiency was obtained in the garden with an intermediate number of obstacles with a value of 0.40 after two hours of work. The estimated energy consumption resulted 0.31 Wh m−2 after one hour and 0.42 Wh m−2 after two hours of working. These results highlight how the correct settings of cutting time may be crucial to consistently save energy during the long period and may be useful for a complete automation of the maintenance of green areas.

Online Coverage Planning for an Autonomous Weed Mowing Robot With Curvature Constraints

Thearea used for grazing cattle constitutes about one-third of the land in United States. In this paper, we present the design of Cowbot, an autonomous weed mowing robot for maintaining cow pastures. Cowbot is designed to operate in rugged environments and provides a cost-effective method for weed control in cow pastures. Path planning for the Cowbot is challenging since weed distribution on pastures is unknown. Given an onboard sensor with a limited field of view, online planning is necessary to detect weeds and plan paths to mow them. We study the general online coverage planning problem for an autonomous mower with curvature and field of view constraints. We develop two algorithms that are able to utilize new information on weed detection to optimize path length and ensure coverage. We deploy our algorithms on the Cowbot and perform field experiments to validate the suitability of our methods for real-time path planning. We also perform extensive simulation experiments which show that our algorithms result in up to 60% reduction in path length as compared to boustrophedon and random-search based coverage paths.

Innovative Living Mulch Management Strategies for Organic Conservation Field Vegetables: Evaluation of Continuous Mowing, Flaming, and Tillage Performances

Organic vegetable production is particularly affected by weed pressure and mechanical weeding is the major tactic implemented by growers to keep weeds under economic thresholds. Living mulch (LM) has been shown to provide several environmental services; however, LM management is required to avoid competition between service crops and cash crops. The aim of this trial was to evaluate two innovative LM-based management systems: a system that provided LM growth regulation by means of flaming (LM-FL) and a system where the LM was regularly mowed by an autonomous mower (LM-AM), both compared with a control without LM and based on standard tillage operations (TILL). The three management systems were evaluated in terms of crop production, weed control, and energy consumption on a 2 yr organic crop rotation of cauliflower (Brassica oleracea L. var botrytis) and eggplant (Solanum melongena L.). LM-AM produced an acceptable fresh marketable yield for both vegetable crops. Moreover, the weed dry biomass obtained in LM-AM-managed plots was lower compared to the LM-FL plots and ranged approximately from 200 to 300 kg ha−1. Furthermore, LM-AM management resulted in lower energy consumption (−2330 kWh ha−1 with respect to the TILL system and −7225 kWh ha−1 with respect to the LM-FL system). The results of this trial suggest that autonomous mowers have a great potential to improve LM management and help with implementing sustainable organic vegetable systems.

Robotic Mowing of Tall Fescue at 90 mm Cutting Height: Random Trajectories vs. Systematic Trajectories

Tall fescue (Schedonorus arundinaceus (Schreb.) Dumort.) is often managed with a cutting height ranging from 70 to 100 mm in ornamental lawns. Some autonomous mowers have been specifically designed to maintain mowing height in the same range. Generally, autonomous mowers operate by following random trajectories, and substantial overlapping is needed to obtain full coverage of the working area. In the case of tall grass, this may cause lodging of grass plants, which in turn may reduce turf quality. The introduction of a navigation system based on systematic trajectories has the potential to improve the performances of autonomous mowers with respect to machine efficiency and turf quality. With the aim of determining the effects of reduced mowing frequency and systematic navigation systems on turf quality and mower performances in terms of working time, energy consumption and overlapping, the performances of two autonomous mowers working with random and systematic trajectories were tested on a mature tall fescue lawn at 90 mm cutting height. The working efficiency was approximately 80% for the systematic trajectories and approximately 35% for the random trajectories; this was mainly due to the lower overlapping associated with systematic trajectories. Turf quality was slightly higher for the mower working systematically (a score of 8 using a 1–9 score with 1 = poor, 6 = acceptable and 9 = best) compared to the one working randomly (quality of 7 and 6 on a 1–9 scale with 1 = poor and 9 = best). No appreciable lodging was observed in either case. For tall, managed lawns, systematic trajectories may improve autonomous mowers’ overall performances.

Evaluation of Autonomous Mowers Weed Control Effect in Globe Artichoke Field

The development of a fully automated robotic weeder is currently hindered by the lack of a reliable technique for weed-crop detection. Autonomous mowers moving with random trajectories rely on simplified computational resources and have shown potential when applied for agricultural purposes. This study aimed to evaluate the applicability of these autonomous mowers for weed control in globe artichoke. A first trial consisting of the comparison of the performances of three different autonomous mowers (AM1, AM2 and AM3) was carried out evaluating percentage of area mowed and primary energy consumption. The most suitable autonomous mower was tested for its weed control effect and compared with a conventional weed management system. Average weeds height, weed cover percentage, above-ground weed biomass, artichoke yield, primary energy consumption and cost were assessed. All the autonomous mowers achieved a percentage of area mowed around the 80% after 180 min. AM2 was chosen as the best compromise for weed control in the artichoke field (83.83% of area mowed after 180 min of mowing, and a consumption of 430.50 kWh⋅ha−1⋅year−1). The autonomous mower weed management achieved a higher weed control effect (weed biomass of 71.76 vs. 143.67 g d.m.⋅m−2), a lower energy consumption (430.5 vs. 1135.13 kWh⋅ha−1⋅year−1), and a lower cost (EUR 2601.84 vs. EUR 3661.80 ha−1·year−1) compared to the conventional system.

Case Study of an Automated Mower to Support Airport Sustainability

This paper documents a case study of an automated mower to support sustainability at an airport. Mowing is an essential component of an airport’s Wildlife Hazard Management Plan (WHMP), which reduces the risk of birds and other wildlife to aircraft operations. Many airports have large areas of land (hundreds or even thousands of acres), which requires significant resources to manage and mow; experience at the Purdue Airport (KLAF) suggests that automated mowing may support economic and environmental aspects of sustainability. Automated mowing supports economic efficiency by reducing personnel requirements, although personnel are still needed for inspections, maintenance, and “mower rescue” if there is a malfunction (technical or field issue). Automated mowing supports environmental impacts by reducing local emissions since the mower is powered by electricity rather than gasoline; this benefit would be increased with the use of solar-powered mowers. Automated mowing may not be viable everywhere, and factors such as terrain, access to available power, acreage, and location on the airfield (including proximity to protected areas) must be carefully considered. Although automated mowing will not completely replace traditional mowing in the near future, autonomous mowers in remote areas may be an appropriate practice to support airport sustainability.

Comparative life cycle assessment and costing of an autonomous lawn mowing system with human-operated alternatives: implication for sustainable design improvements

ABSTRACT Due to recent technological advancements, automation and autonomous solutions are gaining increasing popularity. Yet, a lack of in-depth investigations is noticed on the potential environmental benefits and economic repercussions of implementing autonomous systems. The present study aims to fill part of this gap by quantifying the environmental and economic sustainability of a robotic lawn mower, in comparison with human-operated counterparts. Combining life cycle assessment and life cycle costing methodologies, and by defining adequate functional units, building simulation models, and collecting life cycle inventory data, a systematic comparative study between autonomous and conventional lawn mowers is performed on their environmental and economic impacts. Through this multi-indicator analysis, environmental and economic trade-offs between the autonomous and conventional mowing solutions are quantitatively discussed for key relevant usage scenarios, from mowing an average residential yard to maintaining larger fields like a football stadium or a schoolyard. Concretely, sensitivity analyses on key parameters influencing the performance of the autonomous mower have been conducted to evaluate the environmental and economic benefits of an augmented robotic mower. While optimising the path planning of the current robotic mower would lead to the most substantial savings, improvements on the battery performance, cutting width, and speed of the autonomous solution appear as other promising areas for future work.

Autonomous Mowing and Complete Floor Cover for Weed Control in Vineyards

Enhancing vineyards sustainability and reducing herbicides usage is a crucial theme, thus alternative weed management methods are starting to be studied. Cover crops have been shown to provide for several environmental services such as performing an efficient weed control and promoting biodiversity, thus improving the sustainability of the overall management system. However, the use of cover crops is usually confined to the interrow area in order to avoid competition with vines. Under-trellis weed management in vineyards is an important challenge, conventionally fulfilled by cultivation or repeated herbicides applications. Autonomous mowers are small autonomous machines that have shown a great efficiency when employed in agricultural contexts. Due to their reduced size, they can easily prevent the excessive vertical growth of weeds both in the interrows and under trellis without the use of chemical applications. The aim of this trial was to evaluate if the combination of cover crop species and autonomous mowers management could improve vineyard sustainability. Vineyard floor cover that was managed with an autonomous mower had a shorter canopy height and a lower weed dry biomass compared to the conventionally managed vineyard floor cover. Vineyard floor management providing cover crops and autonomous mowing had a significantly lower weed cover percentage compared to conventional floor management, especially under-trellis. The results of this trial suggest that the combination of cover crops and autonomous mowers may be a sustainable and reliable technique to include in vineyards floor management.

Development of Autonomous Mobile Mowing Robot Using High-Precision GNSS

In this research, we develop an autonomous mowing robot in orchards using high-precision GNSS and a ROS architecture. The robot is equipped with two crawlers, a GNSS module and an antenna, and a 3D-LiDAR. As a high-precision GNSS, Network-RTK-GNSS and CLAS by Quasi-Zenith Satellite System, Michibiki, can be chosen depending on the situation. We investigate the positioning performance of Network-RTK-GNSS in some orchards including outdoor plantations and plastic greenhouses. Some demonstrations in outdoor environments including fallow fields were conducted by the developed autonomous mowing robot.

Identifying obstacles for autonomous mowers in the United States landscape

Identifying obstacles for autonomous mowers in the United States landscape

A Novel Chlorophyll Fluorescence-Based Approach for Mowing Area Classification

Detecting cost-effectively and accurately the working area for autonomous lawn mowers is key for widespread automation of garden care. At present this is realized by means of perimeter wire, which leads to high setup and maintenance costs. Here, we propose an active low-cost sensor approach for detecting chlorophyll fluorescence response. Our novel and innovative sensing concept allows for a robust working area detection. The classification is thereby based on the averaging of multiple measurements using LED pulses and sensed fluorescence responses. By selecting only low-cost consumer components for the sensor design, we allow for high-volume production under low-cost aspects. We evaluated our novel sensor system by analyzing theoretically the signal path. Among other we investigated sampling frequencies, sensed surface areas and environmental influences. In real world experiments, we evaluated the performance of our sensor in an exemplary garden and on collected grass samples. Our theoretical and practical evaluations show that the sensor classification result is robust under different environmental conditions, such as changes in lawn quality.

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

The establishment of permanent cover crops is becoming a common practice in vineyard floor management. Turfgrass science may provide species and techniques with a high potential for improving the sustainability of vineyard floor management. Based on this assumption, an experiment was carried out during 2018 and 2019 at the Donna Olimpia Vineyard, Bolgheri, Italy. The trial aimed at comparing an innovative floor management system based on a turf-type cultivar of bermudagrass mown with an autonomous mower with a conventional floor management system. Ground cover percentage, energy consumption, CO2 emissions, grapevine water status, leaf nitrogen content, fruit yield and must composition have been assessed in order to perform the comparison. The innovative vineyard floor management produced an almost complete ground cover (98%) at the end of the second growing season, with the resident species reduced to a small percentage (4%). Resident species growing under-trellis were efficiently controlled without herbicide applications. A lower primary energy consumption and a reduction in CO2 emissions were observed for the innovative management system compared to the conventional management system. Grapevine water status, leaf chlorophyll content, soil–plant analyses development (SPAD), fruit yields and must composition were similar between the different soil management systems. Based on results obtained in this trial, turf-type bermudagrass and innovative mowing machines may contribute to enhance the sustainability of vineyard floor management.

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

Autonomous mowers are becoming increasingly common in public and private greenspaces. Autonomous mowers can provide several advantages since these machines help to save time and energy and prevent operators from possible injuries. Current autonomous mowers operate by following random trajectories within areas defined by a shallow-buried boundary wire that has the purpose to generate an electro-magnetic field. Once the electro-magnetic field is perceived by the autonomous mower, the machine will stop and change direction. Mowing along random trajectories is considered an efficient solution to manage areas with a variable number of obstacles. In agriculture, autonomous technologies are becoming increasingly popular since they can help to increase both the quantity and quality of agricultural products by reducing productive cost and improving the production process. Thus, even autonomous mowers may be useful to carry out some of the agricultural operations that are highly time consuming. In fact, some autonomous mowers designed and realized to work in vineyards and home vegetable gardens are already available on the market. The aim of this study was to compare the work capacity of six autonomous mowers that move along random trajectories in areas with a high number of obstacles to assess if these machines may be employed in some agricultural contexts. The six autonomous mowers were split in three groups based on their size (large, medium, and small) and were left to work in two areas with equal number of obstacles but different layouts. The first area (Site A) had a square shape and an extension of 23.04 m2, in order to keep the autonomous mowers enclosed inside it. The second area (Site B) had a square shape and an extension of 84.64 m2, in order to have a part of the area with no obstacles. The layout and the size of the two areas affected the autonomous mowers performances in different ways. The six autonomous mowers working on Site A obtained similar results and higher performances compared to the same mowers working on Site B. All the autonomous mowers proved to be able to mow more than 89% of Site A after 2 h and more than 98% of Site A after 5 h. On Site B small size autonomous mowers obtained the best results mowing more than 83% of the area with obstacles after 2 h and more than 98% of the area with obstacles after 5 h. However, specific work settings allowed larger autonomous mowers to improve their efficiency, obtaining similar results compared to smaller autonomous mowers.