Sara Gračić
University of Novi Sad, Faculty of Economics, Segedinski put 9-11, Serbia
The expectation of increasing yields to meet the growing food demand of the increasing population resulted in the new agricultural trend of producing robust machinery combined with precise farm traffic as well as a high price to pay. Constant high pressure on the soil and repeatedly traversing exactly the same route results in concentrated soil compaction damage and machine failures decrease productivity and income. If possible, investments in new machines do not guarantee the increase of goods in the same amount. Farmers work in harsh, even hazardous conditions (pesticides, fungicides and herbicides for plant protection), which have negative impact on their health. On the other hand, science has advanced in the field of robotics, so possibilities and effects of implementing these achievements in agriculture are being examined. Agricultural robots (AGROBOTS) are an extension of a human hand with the goal of replacing him/her in performing difficult tasks and/or in hazardous environments and/or with a variable climate. They can traverse unstructured, unpredictable terrains, while being exposed to the environment. It is expected of them to perform very complex tasks e.g. picking different types, sizes, shapes and colors of fruits, in a highly variable environment where illumination is unequal, locations are random and undefined and climate related factors can drastically worsen working conditions (mud, strong winds, dust, different light settings depending on the position of the sun and the clouds), which will affect their performance. Therefore, it is important to understand the principles of Human-Robot Interaction (HRI), which gives insight into how people and machines can collaborate to achieve desired results. Based on literature review of scientific papers from Google Scholar and Mendeley, the author has identified two problems related to agrobots, which will be in focus of this research. First problem is related to harvesting fruits in real surroundings, because robots are not always able to distinguish a leaf from a fruit. Second problem is that these robots are limited to picking only one type of fruit. To solve these problems, MultiHBot, a robotic model based on HRI was designed. Human controls the picking process via Wi-Fi console through robotic vision, arms and scissors. When a human spots a fruit, he/she instructs the robot to “harvest” it. This ensures that all fruits will be picked, thus maximizing performance which is measured in quantity of picked fruit and revenue. This also means that MultiHBot can be used for harvesting every culture, thus eliminating the need for having different robots for different cultures, with an obvious benefit of cost cutting. MultiHBot could also be used for spraying seeds, if necessary. The robot’s movement along the floor rail is automated and positioning is based on sensors. Combining human intelligence for performing complex part of procedures with robotic automation of simple parts will eliminate physical presence in the field and ensure successful completion of the whole process, increase in productivity and income.
Key words
Agrobots, Human-Robot interaction, process
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