A Review of Robots, Perception, and Tasks in Precision Agriculture
Abstract
:1. Introduction
- costs reductions,
- optimisation of yields and quality concerning the productive capacity of each site,
- better management of the resources, and
- protection of the environment.
Sustainable Development Goals in Agriculture
- Adopting sustainable agriculture techniques that boost productivity and production, aid ecosystem sustainability, and strengthen the capacity to respond to climate change, extreme weather, droughts, floods, and other calamities, as well as progressively increasing land and soil quality. All of this is critical to reaching SDG2’s goals of Zero Hunger by 2030 [24]. Farmers and agricultural organisations who use PA receive access to technologies that help them increase yields, check product quality, enhance crop management, and minimise resource usage costs, all of which help to assure global food security and alleviate hunger.
- By 2030, global water consumption will have increased by more than 50%, with agriculture alone requiring more than can be provided. As a consequence, PA solutions help farmers to manage agrochemicals and minimise the overuse or unnecessary application of fertilisers and pesticides, protecting water and soil quality, in line with SDG6—Clean Water and Sanitation [25] to encourage access to and sustainable management of water and sanitation.
- As part of SDG12—Responsible Consumption and Production [26], the UN is trying to achieve the sustainable management and effective use of natural resources. The PA approach aids farmers in achieving safe management of phytosanitary products and other waste and avoiding the use of harmful substances where possible, reducing their negative effects on soil, water, and air, and thus on human health, as a result of the implementation of active innovation in the development of its products.
- SDG13—Climate Action [27] necessitates immediate measures and activities to address climate change and its implications. The PA methods provide users with tools and technology that not only assure sustainability and increase output and profit, but also allow them to monitor the climate and take appropriate preventative steps to safeguard both fields and the environment.
- Soil degradation is a severe and growing threat due to unsustainable land use and management practices, as well as catastrophic climatic events that introduces a variety of social, economic, and governance challenges. PA works on SDG15—Life on Land [28] targets by encouraging measures that promote land and soil restoration, prevention, and sustainable usage through planned and appropriate crop and field interventions.
2. Review Methodology
3. Enabling Technologies in Precision Agriculture
- Navigation: The vehicle must move in the field independently, following a predetermined course, following key waypoints, and avoiding any obstacles or collisions.
- Sensing: The PA vehicle must be capable of detecting, measuring, and sampling anything that might be relevant in planning crop and soil management operations.
- Mapping: Sensing activities generate a great amount of data, which is generally processed by Geographic Information Systems (GIS), which are maps that collect all essential field features.
- Action: The mapping creates numerous MZs, and then the necessary treatment is carried out in each MZ. As a result, PA vehicles must be equipped to carry out such operations on their own.
3.1. Remote Sensing
- Structural characterisation: Estimating characteristics such as canopy volume, plant height, leaf area coverage, and biomass, among others, allows farmers to make better decisions. A number of researchers [40,41] used canopy volume data to improve pesticide and fertiliser spraying on fruit trees in terms of input savings and environmental costs. Mora et al. [42] also used leaf area coverage for crop-growth monitoring and production prediction, since it reflects various physiological processes in plants. Furthermore, biomass mapping and monitoring enable the identification of changes in plantation conditions due to storms, drought, or diseases [43,44]. Furthermore, because bio-energy from certain crops has become one of the most extensively used energy sources, Kankare et al. [45] were able to use crop biomass as a productivity criterion.
- Plant/Fruit detection: For automated actions such as pruning, harvesting, and sowing to be effective, precision in detecting things of interest in the environment is necessary. To achieve this aim, scientists have used a variety of plant and fruit features and qualities, including colour, shape, and temperature. Colour is a trait that may be used to identify the fruit inside the canopy [46,47] or in the agricultural field [48] in robotic fruit picking or crop harvesting. Furthermore, according to Karkee et al. [49], the morphology of the stems is the property that provides the cutting directions in the majority of instances for automated robotic pruning.
- Physiology assessment: The canopy’s physical response to sunlight produces different spectral patterns that reveal information about the plant’s physiological health. As a result, a number of indices [50,51] based on crop spectral responses have been developed to assess parameters such as nitrogen deficiency, chlorophyll content, water stress, and insect infestation. In addition, numerous sensing tools (for example, infrared gas analysers) enable the direct assessment of a number of physiological characteristics in plants. Many of them need direct contact with the crop, which results in more exact readings; nevertheless, the measuring method takes a unique path, making this technique time-consuming in most cases [52].
3.1.1. Vision-Based Sensors
3.1.2. Range Sensors
3.2. Proximal Sensing
4. Robotics and Agriculture
- The cost of employing robots is lower than the cost of employing any other method.
- Using robots in agriculture improves agricultural production capacities, yields, profits, and survival while also boosting product quality and uniformity.
- The use of robots in growth and production processes minimises uncertainty and volatility.
- In comparison to the conventional method, the introduction of robots allows the farmer to make higher-resolution judgements and/or increase the quality of the output, allowing for growth and production phase optimisation.
- The robot is capable of doing tasks that are either dangerous or impossible to execute manually.
4.1. Flying Drones
4.2. Land-Based Robots
4.2.1. Agricultural Robot Main Functions Taxonomy
4.2.2. Agricultural Robots and Vineyards
4.2.3. Agricultural Robots Classified by Size
4.2.4. Agricultural Robots by Mobility Layout Configurations
5. Collaboration of Multiple Robots in Precision Agriculture
6. Case Study: Agri.Q
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Botta, A.; Cavallone, P.; Baglieri, L.; Colucci, G.; Tagliavini, L.; Quaglia, G. A Review of Robots, Perception, and Tasks in Precision Agriculture. Appl. Mech. 2022, 3, 830-854. https://doi.org/10.3390/applmech3030049
Botta A, Cavallone P, Baglieri L, Colucci G, Tagliavini L, Quaglia G. A Review of Robots, Perception, and Tasks in Precision Agriculture. Applied Mechanics. 2022; 3(3):830-854. https://doi.org/10.3390/applmech3030049
Chicago/Turabian StyleBotta, Andrea, Paride Cavallone, Lorenzo Baglieri, Giovanni Colucci, Luigi Tagliavini, and Giuseppe Quaglia. 2022. "A Review of Robots, Perception, and Tasks in Precision Agriculture" Applied Mechanics 3, no. 3: 830-854. https://doi.org/10.3390/applmech3030049