Robotics and labour in agriculture. A context consideration

Marinoudi, Vasso; Sørensen, Claus G.; Pearson, Simon; Bochtis, Dionysis

doi:10.1016/j.biosystemseng.2019.06.013

Cited by 201 publications

(96 citation statements)

References 35 publications

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“…Some autonomous mowers are equipped with a GNSS positioning system to obtain a "random assisted" pattern [10]. No matter what guidance system is installed, the adoption of autonomous technologies in agriculture helps to increase both the quantity and quality of agricultural products [11,12] and may also help to support a more sustainable economic development [13]. These improvements are mainly exploited for agricultural productive process innovation and for the reduction of productive costs [14].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…The former includes not only variable costs in the process of grain production (such as purchasing seeds, fertilizers, pesticides, rental of agricultural machinery, and land contractual management right), but also fixed assets (such as investment in agricultural machinery and transportation vehicles) [38,39]. The latter includes farmers' labor input, workers, technical services, and information services [37]. There are many factors affecting farmers' willingness to adjust grain production investment, including economic, policy, and natural factors.…”

Section: Analysis Frameworkmentioning

confidence: 99%

“…The odds are 4.89 times higher than farmers who choose to increase investment compared to remaining constant. On the one hand, it shows that an abundant labor force has a significant substitution effect on capital input during busy seasons [31,37]. This also indicates that it is common for rural citizens who are in households with extra laborers, to become part-time farmers and find off-farm employment [50].…”

Section: Factors Affecting Labor Input and Attitudesmentioning

confidence: 99%

“…To the best of our knowledge, no prior work has explored Chinese farmers' investment choice behavior, especially in the Mid-East area of China, from the perspective of farm household characteristics and their attitudes. Secondly, the differences between the farmers' willingness and behavior are probably caused by certain constraints, such as investment capabilities and the substitution effect of input factors [36,37]. However, current literature rarely investigates the association between capital and labor input that can influence investment adjustment behavior.…”

Section: Introductionmentioning

confidence: 99%

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How Farmers Make Investment Decisions: Evidence from a Farmer Survey in China

et al. 2019

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Based on the grain production data hand collected in Mid-East China, a multinomial Logit model was employed to analyze factors that are critical to farmers’ investment decisions in food production. Reasonable explanations are provided to help understand differences between expected farmers’ investments in grain production and the actual results. It was found that the cost of machinery and the number of farmers is key factors affecting farmers’ willingness to adjust investment. Further research shows that most of the farmers who had the willingness to adjust investment did not implement the adjustments in the short-term. From the micro-adaptability expectation perspective, the time that it takes to adjust the planting area could explain farmers’ investment adjustment intention and the behavior. From the macro-investment perspective, short-term output elasticity of physical capital is less than long-term output elasticity. The differences between farmers’ willingness to invest and the actual results are therefore generated. These findings suggest that it is necessary to strengthen the application of big data technology in agriculture in order to improve the platforms’ efficiency in data releasing and reaching out to farmers to provide more accurate advice regarding investment adjustment.

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“…Agricultural robotics represents a great opportunity for farms to face the manual labor outflow from land and the transformation from labor-intensive industry into mechanized plants, both caused by social, technological, and economic matters [1]. Moreover, the introduction of robots can make small-scale operations more feasible, helping small producers not to suffer the current agribusiness model, which requires large resources to pursuit greater yields [2].…”

Section: Introductionmentioning

confidence: 99%

Design of a UGV Powered by Solar Energy for Precision Agriculture

et al. 2020

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In this paper, a novel UGV (unmanned ground vehicle) for precision agriculture, named “Agri.q,” is presented. The Agri.q has a multiple degrees of freedom positioning mechanism and it is equipped with a robotic arm and vision sensors, which allow to challenge irregular terrains and to perform precision field operations with perception. In particular, the integration of a 7 DOFs (degrees of freedom) manipulator and a mobile frame results in a reconfigurable workspace, which opens to samples collection and inspection in non-structured environments. Moreover, Agri.q mounts an orientable landing platform for drones which is made of solar panels, enabling multi-robot strategies and solar power storage, with a view to sustainable energy. In fact, the device will assume a central role in a more complex automated system for agriculture, that includes the use of UAV (unmanned aerial vehicle) and UGV for coordinated field monitoring and servicing. The electronics of the device is also discussed, since Agri.q should be ready to send-receive data to move autonomously or to be remotely controlled by means of dedicated processing units and transmitter-receiver modules. This paper collects all these elements and shows the advances of the previous works, describing the design process of the mechatronic system and showing the realization phase, whose outcome is the physical prototype.

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Robotics and labour in agriculture. A context consideration

Cited by 201 publications

References 35 publications

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

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

How Farmers Make Investment Decisions: Evidence from a Farmer Survey in China

Design of a UGV Powered by Solar Energy for Precision Agriculture

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