Autonomous Mowing and Complete Floor Cover for Weed Control in Vineyards

Sportelli, Mino; Frasconi, Christian; Fontanelli, Marco; Pirchio, Michel; Raffaelli, Michele; Magni, Simone; Caturegli, Lisa; Volterrani, Marco; Mainardi, M.; Peruzzi, Andrea

doi:10.3390/agronomy11030538

Cited by 8 publications

(12 citation statements)

References 44 publications

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“…The average daily growth was around 1 mm per day (0.7 mm) in trial 2, and this low growth rate can be reasonably expected during the fall (Figure A1 in Appendix A). general, autonomous mowers have proven to be a reliable solution for maintaining a constant turf height [48], and these trials confirm these results.…”

Section: Turfgrass Parameterssupporting

confidence: 66%

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

et al. 2021

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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.

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Section: Turfgrass Parameterssupporting

confidence: 66%

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

et al. 2021

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“…Furthermore, a lower above-ground biomass was found in plots managed by the autonomous mower, which usually results in less competition with the crop [51]. This finding may confirm the efficiency of this type of machines for weed control [25]. Moreover, despite the use of the autonomous mower involves a longer working time, the primary energy consumption was lower compared to the flail mower.…”

Section: Discussionmentioning

confidence: 55%

“…Nevertheless, the test was conducted on a well-leveled and not sloping field. In a more challenging agricultural scenario, AM3, being equipped with four-wheel drive, may be more suitable [25].…”

Section: Discussionmentioning

confidence: 99%

“…Details about the above-mentioned assessments are reported in Section 2.3 (Data Collection). Based on previous experience in agricultural contexts, an acceptable weed control effect was achieved when the percentage of area mowed was around 80% [25]. Thus, this level of coverage was assumed as the target of the studied machines.…”

Section: Trial 2: Comparison Between the Weed Control Effect Of Autonomous Mower And Conventional Weed Managementmentioning

confidence: 99%

“…Autonomous mowers moving with random trajectories, despite being developed mainly for lawn mowing, have shown an interesting potential when applied for agricultural purposes, such as weed and cover crop management, both in vineyard [24,25] and horticultural contexts [26,27]. The adoption of these autonomous mowers in agriculture presents several advantages.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Autonomous Mowers Weed Control Effect in Globe Artichoke Field

et al. 2021

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The development of a fully automated robotic weeder is currently hindered by the lack of a reliable technique for weed-crop detection. Autonomous mower 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.

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Design and Simulation of Intra-Row Obstacle Avoidance Shovel-Type Weeding Machine in Orchard

Jia,

Tai,

Wang

et al. 2024

Agriculture

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This paper presents the design of an intra-row obstacle avoidance shovel-type weeding machine. Theoretical analysis of intra-row weeding components guided the determination of the structures and parameters for key parts, including the signal acquisition mechanism, automatic obstacle avoidance mechanism, and weeding shovel. Furthermore, a hydraulic system was designed to support these functions. The design aims to optimize intra-row weeding operations, reduce labor costs, enhance weed control effectiveness, and prevent collisions between weeding equipment and grapevines. Through the construction of a mathematical model, the analysis determined the necessary minimum return speed of the hydraulic cylinder for the intra-row weeding shovel to avoid grapevines. We also established a reasonable range for the extension speed of the hydraulic cylinder to minimize areas missed during weeding. Further analysis showed that using the minimum return speed of the hydraulic cylinder effectively reduced missed weeding areas. A virtual prototype model of the weeding machine was created in ADAMS. Using the coverage rate of weeding operation as the evaluation index, single-factor simulation tests determined that the extension speed of the piston rod in the obstacle avoidance hydraulic cylinder and the forward speed of the weeding machine are the main influencing factors. The preset threshold of the control system, which triggered the automatic obstacle avoidance mechanism when the obstacle avoidance rod reached a specific angle (the “Angle Threshold”), was identified as a secondary influencing factor. Other factors were considered irrelevant. Hydraulic cylinder extension speed, weeding machine forward speed, and angle threshold were chosen as the influencing factors. Following the principles of a Box–Behnken experimental design, a quadratic regression combination experiment was designed using a three-factor, three-level response surface analysis method. The evaluation criterion focused on the coverage rate of weeding operation. A regression model was developed to determine the coverage rate of the weeding operation, identifying the optimal parameters as follows: obstacle avoidance hydraulic cylinder extension speed of 120 mm/s, forward speed of the weeding machine at 0.6 m/s, and an angle threshold of 18°. The optimized coverage rate of the weeding operation achieved 86.1%. This study serves as a reference for further optimization of intra-row weeding machines in vineyards and for other crops.

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Autonomous Mowing and Complete Floor Cover for Weed Control in Vineyards

Cited by 8 publications

References 44 publications

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

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

Evaluation of Autonomous Mowers Weed Control Effect in Globe Artichoke Field

Design and Simulation of Intra-Row Obstacle Avoidance Shovel-Type Weeding Machine in Orchard

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