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The agricultural industry is in transition. And that transition differs country by country, state by state, region by region as well as by type of farming practiced: from primitive to conventional to precision to experimental. A little bit of everything is going on everywhere but the general trend worldwide is toward precision agriculture supplemented by advanced technologies including robotics.
Modern farmers and ranchers are already high-tech. Digitally controlled farm implements are regularly in use. There are partially and fully automatic devices for most aspects of agricultural functions from grafting to planting, from harvesting to sorting, packaging, and boxing.
In some parts of the world, Farmers are already using software systems and aerial survey maps and data to guide their field operations. They also use auto-steer systems included in many new tractors (or buy kits that do the same thing) which follow GPS and software guidance. Some farmers are already transitioning some of their operations to full autonomy.
Artificial intelligence is gaining traction in the agricultural industry and is steadily being integrated in robotics developed for this sector. Conservation agriculture (CA) is an approach that involves crop diversification, permanent soil cover and minimal soil disturbance.
Agricultural robotics can support these environmentally sustainable practices, by allowing spot weeding and precision management of nutrients, pests, diseases and weeds through mechanical removal or spot application of chemicals. Agricultural robots will also be able to substitute arduous labour, especially when there is limited availability, thus increasing social sustainability.
An agrobot can perform a vast array of tasks. The first commercially available agrobots cover three main tasks: eliminating weeds, monitoring pests and diseases, and harvesting specialized crops (berries or vegetables). An agrobot offers cost-saving opportunities as it reduces labour requirements (weeding and harvesting), limits the use of inputs (pesticides) and reduces yield losses resulting from the late detection of pests and diseases
Agri Bots or Agricultural robots are perceptive programmable machines that perform a variety of agricultural tasks, such as cultivation, transplanting, spraying and selective harvesting. There are as many potential uses of agrobots as there are agricultural tasks. Prototypes already exist that can prepare the soil, sow, control pests and harvest cereal crops.
The automation of agricultural equipment can adopt various approaches, from making existing machinery autonomous to developing new autonomous platforms capable of carrying out tasks. These new platforms tend to be very sophisticated and new types of equipment are continuously being developed; however, simple agrobots designed for basic, straightforward tasks can already help farmers with a wide range of operations.
In dynamic and unstructured environments, agricultural robot market can often produce inadequate results due to the inherent uncertainties, unknown operational settings and unpredictability of events and environmental conditions. The level of complexity is closely related to cost and maintenance requirements – as with any technological equipment. The uptake of these technologies at field level requires farmers to adapt their farming practices and capacity accordingly.
Many agricultural robotic advancements use machine vision technology to avoid hazards, identify crops, and even determine if they are ready to be harvested. Machine or computer vision typically involves a camera or multiple cameras feeding information to the robot that allows it to locate and access the crops around it. Machine vision makes it possible for robots to perform tasks like weed picking, growth monitoring, harvesting, sorting, and packing.
In the case of autonomous farm equipment, machine vision and movement sensors work hand in hand to avoid obstacles while navigating the field. The robots create a virtual 3D model of the surface, and with the help of high-resolution cameras, they are able to navigate freely. Automated drone seeders are mostly used in forestry industries right now, but the potential for more widespread use is on the horizon. Planting with drones means extremely hard to reach areas can be replanted without endangering workers.
Combating weeds and making sure crops have room to grow is a constant struggle for farmers. Using computer vision and a variety of mechanical tools, the robot plucks out individual weeds instead of using chemicals. The weed seeker sensors detect the weeds, but rather than applying a spray, the weed-chipper tines activate to mechanically remove the weeds from the earth.
Smart sprayers are typically paired with computer vision cameras to identify weeds for targeted herbicide applications. Sophisticated systems can even identify specific plants and activate only the relevant application nozzles. The Harvest Quality Vision (HQV) is a new technology that allows growers to scan a bin of apples with a camera attachment, which creates a 3D model of the scanned fruit. From these scans, HQV analyses the samples to determine the size, colour profile, and quantity of apples scanned in just moments.
The Global Agricultural Robot Market can be segmented into following categories for further analysis.
Automation and robotics are changing the face of agriculture at an alarming pace. The advantages of agriculture automation are apparent: prices are reduced for consumers, the environmental footprint of farming is significantly reduced, and efficiently reduces labour costs across the board. From self-driving tractors to weeding robots and controlled environment agriculture.
Simple robotic implements utilising basic row-following vision technology are already mature and not uncommon in organic farms. Advances in vision technology are transforming tractor-pulled implements though, upgrading them into intelligent computerized tools able to take plant-specific precise action.
The core technology into the implementation within agriculture automation includes the machine vision, which enables the identification and the localization of specific plants. The algorithms already surpass the capabilities of agronomists in specific cases, e.g., weed amongst cotton. Crucially, the systems are becoming ever more productive, closing the productivity gap with established technology.
Autonomous system integration has been the latest technology being implemented into the Agri based robots wherein in Autonomous navigation is new to tractors. Tractors have been benefiting from tractor guidance and autosteer. Level 4 and Level 5 autonomy within the tractor can autonomously drive outdoors along predetermined GPS coordinates without human intervention.
Machine vision technology can identify and localize different visible fruits against complex and varying backgrounds with a high success rate. The rise of deep learning-based image recognition technologies has caused a leap in performance. Crucially, a clear pathway exists for algorithm development for new fruit-environment combinations, enabling the applicability of machine detection and localization to be extended to many fruits. The robotic path planning, picking strategy and the motion control of the robotic arm are also challenges.
Drones are an increasingly common tool. Currently remote-controlled consumer or prosumer drones are utilized for aerial image acquisition. They have helped reduce the acquisition cost and the resolution of aerial farm images, making the technology accessible to all manner of farmers. Indeed, the hardware platform is now widely available. Automated indoor agriculture is still a new phenomenon, but some companies are making great strides into the industry by using fully automated systems. It is filled with massive hydroponic trays and two cloud-controlled robots that supervise the whole project.
Some of the key vendors of the agricultural robot market include ASIMOV Robotics, AGCO Corporation, International Federation of Robotics, Harvest automation, IFR (Israeli Robotics Association), BARA (British Automation & Robot Association), etc. These players are consistently focused on developing new and advanced robots for agricultural applications.
The industry offers several growth opportunities. Thus, several startups providing innovative products and technologies have been entering the industry. Nexus Robotics launched a weed-yanking robot that helps farmers with soil analysis and environmental monitoring.
In 2018, AgEagle Aerial Systems, Inc. acquired a few assets of Agribotix, LLC, that included Agribotix’ main product, Farmlens. Farmlens is a subscription cloud analytics service that processes data, collected with the help of a drone. Trimble signed an agreement to acquire Müller-Elektronik, a German company focusing on control and precision farming solutions.
In 2017, Deere & Company acquired Blue river technology for USD 305 million. Blue river technology manufactures robots capable of identifying unwanted plants and shooting them with high precision squirts of herbicide. EnerJex Resources, Inc., signed a Merger Agreement with AgEagle Aerial Systems, Inc. The products of AgEagle Aerial Systems, Inc., are designed to enhance traditional farming techniques with the help of Robotics, GPS technology, and high-resolution aerial imagery.
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