Lawn Mower Research Articles

Smart Grass Cutter and Pesticide Sprayer Robot with Mobile Control

Smart Grass Cutter and Pesticide Sprayer Robot with Mobile Control

Design of smart and self-controlled Solar Grass Cutter with Lawn Coverage

In this paper, we design a piece of equipment called the "Variable Head Automatic Solar Grass Cutter.” The system comprises basic components, including a motor drive circuit, control circuit, and solar panel. The overall operation is controlled by an Arduino microcontroller. The proposed system can automatically cut the lawn while adjusting the cutting height according to the surface needs, making it suitable for different types of lawns. The machine's cutting system consists of a DC motor, which drives and controls the rotating edge along a nylon cord, enabling the machine to cut grass with precision and speed. A primary concern of the machine's operation is the safety of the user. To avoid collisions, an ultrasonic sensor is installed on the front of the machine, allowing it to detect and avoid obstacles in its path. This project utilizes solar panels and rechargeable batteries, reducing energy consumption and promoting the use of renewable energy sources. This makes the machine eco-friendly and cost-effective. Consequently, this machine provides an opportunity to promote progress in innovation and maintenance.

Why mow?: A review of the resulting ecosystem services and disservices from mowing turfgrass

AbstractTurfgrasses are those grasses that tolerate frequent mowing. The act of mowing turfgrasses, primarily lawn mowing, has received much negative attention primarily due to its labor requirement and the resulting mower emissions. This paper provides a comprehensive review of the benefits and drawbacks of mowing grasses, specifically turfgrasses used on lawns, parks, golf courses, and sports fields, using an ecosystem services and disservices framework. Discussed is the challenge of creating a “one‐size‐fits‐all” approach to selecting the best mowing management practices and sociocultural tensions that exist related to lawn mowing. Discussion also includes the benefits and value gained from mowing turfgrass and strategies to mitigate ecosystem disservices that result from mowing.

Robust adaptive event-triggered control for unmanned surface vessel–unmanned aerial vehicle: Application to sea–air synchronized lawn mowing search operation

This paper investigates a robust adaptive event-triggered control algorithm with a consideration of the synchronized lawn mowing search guidance for a heterogeneous system comprising both an unmanned surface vessel (USV) and an unmanned aerial vehicle (UAV). For ensuring a cooperative global search navigation of the USV–UAV, a synchronized lawn mowing search guidance is developed with two key elements: the L1-based virtual ship (L1VS) and L1-based virtual aerial (L1VA), where the former can generate the smooth reference path for a USV according to the search task scope, while the latter can program the reference path for a UAV on the basis of its search requirements (search speed, detected capacity and communication distance). In the control loop, a robust adaptive path following control law is designed by utilizing an event-triggered mechanism and a minimal learning parameter (MLP) technique. In particular, the event-triggered mechanism has a potential role for a reduction of the unnecessary transmission resource usage for the channel of the controller to the actuator. Besides, only one learning parameters on each channel by introducing the MLP technique, implying a lower computational burden. Through the Lyapunov theorem, the semi-global uniform ultimate bounded (SGUUB) stability properties of the proposed control system. Finally, two numerical simulations are carried out to evaluate the effectiveness of the proposed strategy and the advantages compared with existing techniques.

Factors affecting the adoption of farm mechanization in Rupandehi, Nepal

Agricultural mechanization is pivotal in farmer’s fields as it functions more efficiently and helps increase farm productivity. Despite the massive involvement of people in agriculture, farm productivity is relatively low. One main reason for this is the staggered implementation of farm mechanization. This paper aims to explore the factors affecting the adoption of farm mechanization using the Chi-square test and identify the major problems using relative frequency values. A total of 112 respondents, 28 each from 4 municipalities of Rupandehi district were interviewed based on stratified random sampling technique. The results showed that the adoption rates of various farm machinery were notably high, with tractors, cultivators, mills, and sprayers being universally employed by 93.75 % of the surveyed individuals. The government subsidies to only 7% of farmers facilitate machinery procurement. The size of the total cultivated land was found to be significant over the use of harvester, grass cutter, and power tiller, and owing of milling machine. The availability of subsidies and owning of mills were found inter dependent. The annual expenditures of farmers and their access to theCusto m Hiring Centre were found to be significant. Lastly, with index values of 0.402 and 0.393, the high costs of farm machinery and small land holdings were major problems in the adoption of farm mechanization. Therefore, addressing the high initial costs of modern farm equipment, providing targeted subsidies, innovative institution formation to provide better services to marginalized farmers, and expanding extension services are essential steps to promote the adoption of farm mechanization.

Phenological Analysis of Grasses (Poaceae) in Comparison with Aerobiological Data in Moscow (Russia).

Grasses (Poaceae) produce large amounts of pollen and are among the main causes of pollinosis worldwide. Despite their morphological similarity, pollen grains of different grass species may have different allergenicities. Therefore, quantification of the roles of individual species in airborne pollen is an important task. There are very few studies on this topic, and none of them have been conducted in a temperate continental climate. Our study was carried out for three years (2020-2022) in the urban territory of Moscow (Russia) and aimed to understand what grass species contribute the most to the total pollen load of the atmosphere. The comparison of aerobiological and phenological data was based on calculating the phenological index, which is a combination of phenological parameters, pollen productivity of individual species, and their abundance. Our data showed that the decomposition of pollination curves based on the phenological index was sometimes very efficient but not always possible in temperate continental climates. The main reasons for disagreement between aerobiological and phenological data were weather conditions and lawn mowing. Not all grasses were equally important as sources of allergenic pollen. The greatest contribution to the pollen load at the beginning of the season in Moscow was made by Dactylis glomerata, and to a lesser extent by Phleum pratense and Festuca pratensis. These are the most common species, which are widespread throughout Europe. The contribution of minor components is insignificant.

Customized Plant Growth Promotion with Soil- and Cultivar-Compatible Microbial Biofertilizers

Organic fertilizers and microbial biofertilizers are now widely recognized to effectively complement traditional mineral fertilizers for plant growth. The present study shows that bio-organic fertilizers can be enhanced by the addition of functional plant-growth-promoting rhizobacteria (PGPR) that provide additional benefits to plants. We hypothesized that not all beneficial soil bacteria are functional in different farm soils and plant varieties; hence, the most effective PGPR that are suitable to each farm’s individual cropping conditions were selected. Five different field soils and their respective crops were tested for compatibility with six microbial biofertilizers (including three new bacterial strains) to supplement a commercially available bio-organic fertilizer. In pot trials with lucerne plants, four out of the six microbial treatments led to significant (p < 0.05) growth promotion benefits (up to 79.8% more leaves and dry weight) compared to mock-treated or bio-organic fertilizer-only-treated control plants. A trial with industrial hemp demonstrated that compatibility with PGPR occurs in a cultivar-specific manner, leading to growth promotion ranging from −3.4% to 68.9%, with each cultivar displaying a preference for a different PGPR. Finally, pot trials with Rhodes grass and two different soils demonstrated high yield increases compared to control plants, with Bacillus amyloliquefaciens 33YE being most effective for one soil and Bacillus velezensis UQ9000N/Pseudomonas lini SMX2 for the other soil. Yield advantages reduced after several cuts of grass, but a repeat biofertilizer treatment at 69 days after the initial treatment restored high yield advantages, with the same PGPR again being most effective. These results demonstrate the importance of customization of microbial inoculants to identify the most compatible PGPR–cultivar–soil interaction. The customization of microbial biofertilizers to soils and plant cultivars, combined with complementary fertilizer applications, can potentially lead to more reliable and more sustainable agricultural practices.

基于S-TEB算法的果园割草机人局部路径规划研究

This paper proposes a local path planning algorithm method named S-TEB (Smooth Time Elastic Band), aimed at fulfilling the requirement of full coverage for ORLMs (Orchard Robotic Lawn Mowers) during mowing operations. Firstly, by analyzing the tracking control mode of ORLMs in operational scenarios, control points are selected reasonably. Subsequently, utilizing B-spline curves, the path is optimized to generate the optimal trajectory and speed for ORLMs that satisfy multiple objectives and constraints. Finally, multiple simulations and field experiments were conducted in actual operational environments, with a speed of 0.6 m/s. Experimental results show that in scenarios involving obstacle avoidance, the minimum distance between the automatic lawnmower and the outer contour of obstacles is 4 cm. Compared to the traditional TEB planning algorithm, there is a 4.23% increase in mowing coverage area. These findings provide theoretical and technical support for local path planning in the operational scenarios of ORLMs.

Sustainability of athletic field turf comparing organic and synthetic practices under two heights of cut

AbstractLong‐term comparisons over several years between organic and synthetic management are lacking in sports turf research. Our objective was to investigate playing surface qualities and soil properties over an 8‐year period. For this trial, Kentucky bluegrass (KBG, Poa pratensis L.) sod was established and annually inter‐seeded with perennial ryegrass (Lolium perenne L.) and KBG. Factors included height of cut (3.2 and 6.4 cm) and management systems (MSs; synthetic and organic) with three replicates. Synthetic practices included chemical fertilizers and pesticides, while the organic system used hand‐weeding and biological fertilizers (leaf compost and naturally derived organics) with biological controls. In all years, wear was simulated in the fall using a slip‐wear machine and evaluated for playing qualities including visual wear tolerance, ball bounce (BB), surface hardness, and traction. Soil properties were evaluated in some years including pH, soil organic matter (SOM), soil bulk density, soil aggregate stability (SAG), and soil available P. Both MS received the same total N of 196 kg ha−1 year−1 but P applied varied with the MS (synthetic, 7.6 kg ha−1 year−1; organic, 23.2 kg ha−1 year−1). Synthetic practices provided acceptable visual wear tolerance (1–9, ≥6 acceptable) in 4 of 8 years compared to only 1 year for organic practices. Shorter cut grass (3.2 cm) consistently provided better visual wear tolerance (average = 5.6), harder surfaces (average = 51 g), and higher BB (average = 35.8%) consistent with accepted player standards. Synthetic practices afforded better tolerance to wear compared to organic practices in 5 of 8 years but little difference was observed in the other surface properties. Organic practices were consistently above 6.0 in soil pH (higher by 12%), 20% higher in soil available P, 25% higher in SOM, and with lower soil bulk density. SAG was higher following 8 years of simulated traffic by the last year of the test under organic practices. Results suggest competing benefits with synthetic practices affording better wear tolerance while organic practices promote better soil health.

Adding a mosaic mowing regime to urban lawns is the key to city biodiversity management for pollinators

City populations are growing rapidly, with built-up areas occupying ever-larger areas within the cities. One of the last green places in a city is urban lawns. Our study aimed to investigate how lawn management changes can contribute to improving insect pollinator biodiversity at the city scale. Over two years, we studied dozens of urban lawns in Prague (Czech Republic) that were partially left unmown, and we selected three major groups of pollinators: Lepidoptera, Coleoptera and Hymenoptera. This study showed that leaving unmown lawn areas has a strong positive effect on insect biodiversity. The high intensity of lawn flowering through the vegetation season was also crucial. Our research showed that leaving unmown parts of urban lawns is one of the key amendments to maintain or even increase pollinator biodiversity in cities. It also appears to be the best way to attract red-listed species. A significant reducing mowing frequency to achieve a higher flowering intensity should be a positive solution. So-called insect gardening by reducing urban lawn mowing frequency or leaving parts of lawns completely unmown can help not only pollinators but also other animals that find food or shelter in them. This management will also enable the propagation of flowering plants. Additionally, biodiversity measures coincide with reducing evapotranspiration and thus cooling urban heat islands.

Assessing the Evolution of Stability and Maturity in Co-Composting Sheep Manure with Green Waste Using Physico-Chemical and Biological Properties and Statistical Analyses: A Case Study of Botanique Garden in Rabat, Morocco

Organic waste utilization stands as a pivotal approach to ecological and economic sustainability. This study aimed to assess the stability, maturity, and evolution of co-composts comprising various blends of green waste (GW) and sheep manure (SM). Employing a diverse array of physico-chemical and biological parameters, we investigated the co-composting process over 120 days. Three types of garden waste (mixture of green waste (MGW), fallen leaves (FL), and grass cutting (GC)) were utilized. The results revealed significant compost transformation, evident by odor and insect absence and a shift to dark brown coloration, indicating maturation. The compost C2, derived from FL, exhibited superior soil amendment potential. Significantly, it exhibited a pH level of 6.80, an EC of 2.45 mS/cm, and an OM content of 55%, along with a C/N ratio of 16.15. Analysis of the macronutrients revealed values of 1.98% for TN, 3.22% for TP, and 0.61% for K. Crucially, the compost showed no phytotoxic effects and boasted a high GI of 94.20% and a low respiration rate of 4.02 mg/50 g, indicating its stability and appropriateness for agricultural application. Our findings underscore compost’s potential as an eco-friendly soil amendment, offering valuable insights for sustainable agricultural management and supporting the circular economy.

Characterization of First Cut Alfalfa and Grass Silage Management Practices on Canadian Dairy Farms

Characterization of First Cut Alfalfa and Grass Silage Management Practices on Canadian Dairy Farms

Development of a Solar-Powered Robotic Lawn Mower

Lawn keeping has been a major issue in campus environment due to rising cost of diesel fuel and lack of man power to operate both tractor-mounted and motorized lawn mowers. An automated solar-powered robotic lawn mower was developed in this research work to solve this problem. The components of the mower include a frame, three caster wheels, two gear motors which provide the forward motion, a 12v DC cutter motor which rotates the cutting blade, 2202mAH limpo battery for power supply, a 16W solar panel for charging the battery, a charge controller, a Raspberry Pi 3 B+ microcontroller which controls the motors, and a VNC mobile app for setting inputs for control. The mover was locally fabricated at the Agricultural Engineering workshop of The Federal Polytechnic, Ado-Ekiti, and it was tested in an open field. The effective field capacity and field efficiency of the machine were found to be 0.13 m2/s and 88% respectively. The total cost of producing the mower was 185,800 naira. The mower is recommended for large scale production and for usage on campuses.

Smart Lawn Bluetooth Mower with Sprinkler and Time Tracker

Abstract: This abstract outlines the development of a multifunctional lawn care device that amalgamates a traditional lawn mower with an integrated water sprinkler, hence revolutionizing lawn care. It not only cuts down on manual labor in one but many ways. This lawn mower simultaneously supports the irrigation of lawns, enhancing convenience. What comes to more ease is the control of the machine via Bluetooth module, which can be operated with a smartphone through an application. It also shows the estimated mowing time and brushes off the residue to make the mowing activity more organized. Using ESP32 for Bluetooth control, it manages to move in the right direction and start and stop when required. This device merges the conventional task of mowing with an innovative sprinkler system in order to irrigate the lawn as and when required. The built in time tracker allows users to schedule and automate lawn care routines optimizing maintenance efforts and promoting healthier greener laws while saving both time and resources. This integration of lawn care functionalities aims to enhance convenience and effectiveness in maintaining outdoor spaces, manage to cut down on labour and cost and give a user-friendly experience.

Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor Based on RPLESO

In view of the problem of the low-speed jitter of household lawn mowers driven by a permanent magnet synchronous motor (PMSM) at low speeds and high torque, and the complicated parameters of traditional non-linear active disturbance rejection controllers, a partially optimized linear active disturbance rejection control (LADRC) driving PMSM strategy is proposed. First, the linear extended state observer (LESO), which bears a significant burden in terms of speed and load estimation in active disturbance rejection control, is optimized by reducing its order to improve the anti-disturbance performance of the active disturbance rejection controller within a limited bandwidth. Secondly, the reduced-order parallel linear extended state observer (RPLESO) is obtained by optimizing the parallel structure of the order-reduced LESO, which improves the control precision and robustness of the system. Through a simulation and experimental verification, the optimized LADRC control of the PMSM system is shown to improve the parameter adjustability, speed estimation precision and system robustness.

Robotics Autonomous Systems (RAS) in Food Laboratories are the Future of Food Processing Industries: A Review

Recent advancements in robotics have witnessed significant progress in both industrial and mobile robotics, paving the way for a new era of automation. However, a paradigm shift is underway in robotics research, focusing on enhancing the interaction between humans and robots, termed as service robotics. This emerging field aims to cater to a wide array of human social needs by bridging the gap between man and machine. Traditionally, laboratory automation has been constrained by the rigid control mechanisms of computer-driven robots. Despite their utility, particularly in liquid handling tasks, many laboratory procedures remain only partially automated. Nonetheless, by breaking down laboratory processes into discrete unit operations and integrating them, overarching analysis schemes can be accomplished. The future of laboratory automation necessitates interdisciplinary skills, requiring scientists to blend biological knowledge with engineering expertise to fully exploit its potential. Simultaneously, a new wave of robotic innovations is permeating various sectors, from robot lawn mowers to autonomous vehicles, alongside smarter robots in manufacturing environments. This progression underscores the increasing reliance on automation, with future research endeavours expected to pivot towards leveraging laboratory automation to tackle novel scientific challenges. This abstract underscore the necessity for future scientists to acquire a comprehensive skill set that integrates both biological knowledge and engineering expertise. It highlights the trend towards greater automation in laboratory environments, representing the merging of scientific and engineering fields to tackle new research challenges.

A Full-Coverage Path Planning Method for an Orchard Mower Based on the Dung Beetle Optimization Algorithm

In order to optimize the operating path of orchard mowers and improve their efficiency, we propose an MI-DBO (multi-strategy improved dung beetle optimization algorithm) to solve the problem of full-coverage path planning for mowers in standardized quadrilateral orchard environments. First, we analyzed the operation scenario of lawn mowers in standardized orchards, transformed the full-coverage path planning problem into a TSP (traveling salesman problem), and mathematically modeled the U-turn and T-turn strategies based on the characteristics of lawn mowers in orchards. Furthermore, in order to overcome the issue of uneven distribution of individual positions in the DBO (dung beetle optimization) algorithm and the tendency to fall into local optimal solutions, we incorporated Bernoulli mapping and the convex lens reverse-learning strategy in the initialization stage of DBO to ensure a uniform distribution of the initial population. During the algorithm iteration stage, we incorporated the Levy flight strategy into the position update formulas of breeding beetles, foraging beetles, and stealing beetles in the DBO algorithm, allowing them to escape from local optimal solutions. Simulation experiments show that for 18 types of orchards with different parameters, MI-DBO can find the mowing machine’s operation paths. Compared with other common swarm intelligence algorithms, MI-DBO has the shortest average path length of 456.36 m and can ensure faster optimization efficiency. Field experiments indicate that the algorithm-optimized paths do not effectively reduce the mowing machine’s missed mowing rate, but the overall missed mowing rate is controlled below 0.8%, allowing for the completion of mowing operations effectively. Compared with other algorithms, MI-DBO has the least time and fuel consumption for operations. Compared to the row-by-row operation method, using paths generated by MI-DBO reduces the operation time by an average of 1193.67 s and the fuel consumption rate by an average of 9.99%. Compared to paths generated by DBO, the operation time is reduced by an average of 314.33 s and the fuel consumption rate by an average of 2.79%.

Solar Grass Cutter

A Solar grass cutter is a machine that uses sliding blades to cut a lawn, that help human to cut grass automatically. Even more sophisticated devices are there in every field. Due to rapid development, many robots have turn into an autonomous robot. Power consumption becomes essential for future. The movement or the path of the Solar grass cutter is based on a path planning technique. Solar grass cutter is a very useful device which is very simple in construction. It is used to maintain and upkeep lawns in gardens, schools, college’s etc. In our project, we are using Arduino UNO, Bluetooth module, DC motor, solar panel. For this grass cutter, Arduino UNO microcontroller is utilized as the microcontroller. Sensors are used to provide feedback from outside world. We have made some changes in the existing machine to make its application easier at reduced cost. Our main aim in pollution control is attained through this. Unskilled operation can operate easily and maintain the lawn very fine and uniform surface look. Every action of the grass cutter is monitored by the ARDUINO UNO with the help of the sensors and Bluetooth module. In our project,―Solar grass cutter is used to cut the different grasses for the different application

Research on a Low-Cost High-Precision Positioning System for Orchard Mowers

To regulate the energy flow in orchard ecosystems and maintain the environment, weeding has become a necessary measure for fruit farmers, and the use of automated mowers can help reduce labor costs and improve the economic efficiency of orchards. However, due to the complexity of the geographic and spatial environment of the orchard, in particular, the loose and undulating road surface, the interference of satellite signals by large trees, etc., which decreases the positioning accuracy and stability of the positioning system of the mower, and the high cost of the sensor also affect the popularization of intelligent mowers for these applications. To address the above problems, this paper constructs a positioning system through a low-cost global navigation satellite system (GNSS), inertial measurement unit (IMU), and odometry, and utilizes the Kalman filter algorithm based on the error state for a combined GNSS/IMU positioning so that the inertial navigation system can maintain a more accurate positioning when the GNSS signals are poor. Considering the side-slip and error accumulation problems of the odometry of the traction mower, the combined GNSS/IMU positioning information is used to optimize the odometry model and improve the navigation and positioning accuracy. To reduce the measurement error of the IMU and the problem of error accumulation, this paper utilizes the nonholonomic constraint (NHC) of a lawn mower to suppress the dispersion of IMU measurement errors and constructs periodic and nonperiodic zero-velocity updating (ZUPT) strategies in combination with the travel paths of lawn mower navigation operations in the region to update the IMU data to improve the positioning accuracy and stability of the positioning system. The experiments show that the average error of the constructed positioning system is controlled within 0.15 m, the maximum error is maintained at approximately 0.3 m, and the positioning system constructed by using low-cost sensors can achieve a positioning accuracy similar to that of the differential global navigation satellite system (DGNSS), which is beneficial for the promotion and application of intelligent mowers in orchards.

FULLY AUTOMATED SOLAR GRASS CUTTER

In present world grass cutter machines are becoming very popular . Rapid growth of different high-tech tools and equipment makes our jobs much easier . Nowadays we are facing issues of pollution and power failures in our daily life . As we know pollution is manmade, so there are solutions for this problems too .Earlier grass cutters contains IC engine and hence because of its environmental impact, pollution level rises .IC engines are costly and hence the grass cutter is also costly.This was one of the main disadvantage of old model grass cutters. Maintenance cost of this conventional machine is also high.In order to overcome these drawbacks , we have thought about the device, which performs its functions without causing such problems.The project aims at implementing a grass cutting machine system which runs on solar energy .This model is economical compared to the previous one .Solar power doesn’t release any green house gases.Hence it is safe and environmentally friendly. Also use of solar power reduces use of electricity .General principle of mowing were used in the designinig and developing of solar powered grass cutter .The designing of the project consists of solar panel,DC motor,motor driver,arduinoUNO,cutting blade,ultrasonic sensor.Arduino is used to control the entire system and hence the device is automated.Ultrasonic sensor is used for avoiding obstacles and the working of the same is also controlled by the microcontroller.The battery recharges by the solar charging controller and also less energy is required for cutting the grass.Hence the performance is more efficient than the conventional machine.Levelling of grasses in playgrounds,gardens etc.can be achieved by using this machine.The cutted grass left behind will also be collected along with the cutting operation by using grass collection technique.This is additionally inbuilted on the device.Since the device is fully automated no man power is needed and also skilled labourers are not neeeded to operate the device.Hence normal people can use this automated grass cutter without much efforts. Keywords-Solar,Grass cutter,Levelling,Economical,Pollution- Free