In our previous entries we outlined the current issues and future prospects of smart farming and agriculture automation. Now let’s take a closer look on the present state of agriculture robotics. In 2020, the global agricultural robots market reached a value of USD 5.4 billion and is expected to grow by a compound annual growth rate (CAGR) of 25.50% from 2021 to 2026. This means a projected 16-billion-dollar increase in just 5 years. What present-day innovations affect this excellent prognosis?
Agricultural drones have already proved to be extremely useful in optimizing farm yield. From spraying substances, such as pesticides and liquid fertilizers, to field mapping, weed control, seeding and planting, drones can be used to improve many aspects of field operations. In addition, the flyover images of the crops are immensely helpful in gathering important data concerning crops’ growth and health, especially when combined with advanced diagnostic systems based on computer vision and machine learning. Let’s take a look at two high-profile examples:
- Quantix VTOL from AeroVironment is a hybrid drone equipped with the AeroVironment Decision Support System designed to help precision farming. Thanks to special sensors and multispectral imagery capabilities, Quantix is extremely well-suited for crop scouting and can survey up to 160 hectares in 45 minutes. See more here: https://www.youtube.com/watch?v=o0nNBUC3ZNQ
- Agras T20 from DJI is a drone designed for autonomous operations over variety of terrains, such as farmlands, orchards, and terraces. Thanks to the built-in Omnidirectional Digital Radar and Autonomous High-Precision Operation System, Agras T20 proves very efficient in precision spraying. See more here: https://www.youtube.com/watch?v=hGyLjO7KWeU
Although automatic harvesters are still not that common due to relatively high entry costs, it is certainly a market with a bright future, especially considering the growing seasonal labor shortages and extremely high efficiency of harvesting automatons. The field robots can work around the clock, reduce waste, and help with data collection. Thanks to advanced computer vision systems they are able to identify mature fruit and vegetables as well as avoid damaging the unripe specimens. These functionalities used to be considered unfeasible for machines, but are now a reality. Here are some great examples:
- Automatic apple picker from Abundant Robotics uses computer vision and AI to identify ripe apples and then sucks them into a bin with a special vacuum without damaging other fruits. It’s the first commercial apple harvester actually available on the market. See more here: https://www.youtube.com/watch?v=aijzVv6UeLQ
- Autonomous Tomato Harvesting Robot from Inaho also uses AI algorithms to recognize ripe fruits by color and size. It can work both in day- and nighttime and lasts up to 12 hours on a single charge. Thanks to SLAM, RTK GPS and sensor technologies, the robot can navigate without the help of human operator. See more here: https://www.youtube.com/watch?v=tcfEtP130fo&t=82s
At Contee, we are currently hiring for a team working on a similar robot: an automated asparagus harvester. Once fully developed, it should be able to harvest almost 3000 asparagus per hour, using advanced image processing technology combined with machine learning to accurately identify ripe specimens and a special harvesting tube to collect the asparagus without damaging other plants. We expect it to be able to process more than 5 hectares of asparagus crops per season, replacing several dozens of workers and substantially reducing the overhead costs.
As you can see, automation of farming operations is a subject worth exploring — especially since it’s said to be the future of agricultural sector. To learn more about its practical applications, check our previous entry on this subject here.