By submitting this form, you are agreeing to the Terms of Use and Privacy Policy.
An agricultural robot, also known as an agrirobot or agbot, is a type of robot designed specifically for use in agricultural applications. These robots are equipped with various sensors, actuators, and other technologies to perform tasks traditionally carried out by humans or heavy machinery on farms. Agricultural robots are typically autonomous or semi-autonomous, meaning they can operate with minimal human intervention.
There are several types of agricultural robots:
Benefits of agricultural robots include increased efficiency and productivity, reduced labor costs, optimized resource use (such as water and fertilizer), and improved crop yield and quality. These robots can also mitigate the effects of labor shortages and minimize the risks associated with manual labor, such as exposure to harmful chemicals and repetitive strain injuries.
However, there are also risks and challenges associated with the adoption of agricultural robots. High initial investment costs and ongoing maintenance expenses can be prohibitive for some farmers, especially those with smaller operations. Technological complexities and the need for specialized skills to operate and maintain these robots may pose challenges for adoption.
Additionally, concerns about data privacy and security arise due to the collection and use of sensitive agricultural data by these robots. Moreover, regulatory hurdles and the need for standards and guidelines for the safe deployment of agricultural robots present further challenges to widespread adoption in some regions.
Despite these challenges, the continued advancement of technology, coupled with increasing awareness of the benefits of agricultural robots, is expected to drive their adoption and integration into farming practices globally.
By Geography:
By Type:
By Application:
By Offering:
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, 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.
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 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.
