Fleets of robots for environmentally-safe pest control in agriculture

Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops

Development of New Cotton Defoliation Sprayer Using Unmanned Ground Vehicle and Pulse Width Modulation Technology

Chemical spraying is one of the most important and frequently performed intercultural agriculture operations. It is imperative to utilize appropriate spraying technology as a selection of ineffective one leads to waste of agrochemicals to the non‐target area. Several precision technologies have been developed in the past few decades, such as image processing based on real‐time variable‐rate chemical spraying systems, autonomous chemical sprayers using machine vision and nozzle control, and use of unmanned aerial and ground vehicles. Cotton (Gossypium hirsutum L.) is an important industrial crop. It is a perennial crop with indeterminate growth habit; however, in most parts of the United States, it is grown as an annual crop and managed using growth regulators. Cotton defoliation is a natural physiological phenomenon, but untimely and/or inadequate defoliation by natural processes necessitates the application of chemical defoliants for efficient harvest. Defoliation is a major production practice influencing harvester efficiency, fiber trash content, cotton yield, and fiber quality. Currently, defoliant spraying is done by conventional ground driven boom sprayer or aerial applicator and both systems spray chemical vertically downwards into the canopy, which results in less chemical reaching the bottom of the canopy. Thus, a new autonomous ground sprayer was developed using robotics and pulse width modulation, which travels between two rows covering the whole canopy of the plant. Field research was conducted to evaluate the (i) effect of duty cycles (20%,40%, and 60%) on droplet characteristic (droplet distribution, deposition, and drift potential), defoliation cotton fiber and (ii) effect of duty cycles on cotton yield and II fiber quality. Droplet characteristics (droplet distribution, density, and potential droplet drift) were non-significant across the treatments and results from the water‐sensitive paper field test showed adequate penetration with low flow rates. Therefore, a 20% duty cycle was sufficient to defoliate based on the result of the field experiment. Likewise, the defoliants could be applied safely at the duty cycles tested without influencing fiber quality except for nep/gm, length (Ln), L (5%), short fiber content (SFCn), trash content in field 1 and micronaire, nep size, length (Ln), span length (5%), SFC, and fiber fineness in field 2 which were significant. However, the 20% duty cycle significantly reduced the amount of defoliant and would be a good choice for the autonomous cotton defoliation. This is a significant development as there is a huge potential to save on the cost of applying defoliant chemicals and the environment

Task-based agricultural mobile robots in arable farming: A review

In agriculture (in the context of this paper, the terms “agriculture” and “farming” refer to only the farming of crops and exclude the farming of animals), smart farming and automated agricultural technology have emerged as promising methodologies for increasing the crop productivity without sacrificing produce quality. The emergence of various robotics technologies has facilitated the application of these techniques in agricultural processes. However, incorporating this technology in farms has proven to be challenging because of the large variations in shape, size, rate and type of growth, type of produce, and environmental requirements for different types of crops. Agricultural processes are chains of systematic, repetitive, and time-dependent tasks. However, some agricultural processes differ based on the type of farming, namely permanent crop farming and arable farming. Permanent crop farming includes permanent crops or woody plants such as orchards and vineyards whereas arable farming includes temporary crops such as wheat and rice. Major operations in open arable farming include tilling, soil analysis, seeding, transplanting, crop scouting, pest control, weed removal and harvesting where robots can assist in performing all of these tasks. Each specific operation requires axillary devices and sensors with specific functions. This article reviews the latest advances in the application of mobile robots in these agricultural operations for open arable farming and provide an overview of the systems and techniques that are used. This article also discusses various challenges for future improvements in using reliable mobile robots for arable farmin