Drones - Agri-EPI Centre - Engineering Precision Innovation

Drones

An unmanned aerial vehicle (UAV) drones take pictures and videos from the air. Combined with emerging camera technology, drones now form an established and growing part of modern agriculture.Agri-EPI explores and delivers precision farming engineering, technology and innovation in the UK agriculture across soil, crops and livestock. Find out more about drones and how they are being used to support better farming in the UK and around the world today.

Spectral imaging for the agriculture industry

Spectral imaging as a general concept combines characteristics of imaging and spectroscopy technologies. Optical spectral imaging particularly makes use of visible, near infrared and short-wave infrared spectral range, has been demonstrated to be a very powerful tool in identifying, classifying, and mapping specific targets across whole scenery image in various application scenarios.

Spectral Imaging is especially useful in the agricultural domain, where crop/vegetation in different conditions has unique spectral characteristics. With more robust and rugged imaging product integrated with various platforms, agri-tech has been undertaking revolutionary improvements for remote sensed inspection. Multispectral imaging, hyperspectral imaging, and SIF (solar-induced fluorescence) imaging can be broadly derived depending on spectral bands and resolution needed.

Eliot Dixon, Head of Engineering at Agri-EPI Centre said:
“We have established a strong sensing team within the company, able to deploy a range of spectral imagers into agriculture including some exciting unique capabilities. With our contextual farm data, storage facilities and analysis tools this is a key data service for developers which is available to all.”

Multispectral Imaging
The advantage of multi-spectral imaging is that it extends human sight sensitivity beyond visible spectrum. Some wavelengths that are widely recognized for particular applications, such as normalized difference vegetative index (NDVI), can be deployed into multi-spectral imaging. Nonetheless, it has been proven to be very useful in many other fields, greatly empowering advancement of agriculture. And the adoption of UAV has made it possible to make large-scale mapping and thus better agricultural management.

Agri-EPI Centre has invested MicaSense Altum sensor covering RGB, NIR, Red Edge and LWIR, which can be operated easily on VTOL UAV platform.

With this multi-spectral imaging system, several important vegetation indexes such as red edge, NDVI, can be quickly collected and mapped across survey fields.

Hyperspectral Imaging
Hyperspectral imaging captures images at hundreds of wavelengths, creating a detailed spectral signature of objects and materials. Compared to multispectral imagery, hyperspectral imagery measures energy in narrower and more numerous bands, thus giving much more information on target. Hyperspectral image data is a datacube, where each pixel holds full spectrum across the range. Since spectra are as unique as ‘fingerprint’ to target, hyperspectral imagery can unveil features that multispectral may miss out.

Agri-EPI Centre has invested in a range of hyperspectral imaging systems. Read below for more:

Spectral imaging brochure

Automation and robotics for agriculture at Agri-EPI Centre

Agri-EPI, the centre for precision innovation in farming, is a first choice for agri-tech developers, from start-ups right through to established companies, to help with creating robust and commercially viable agricultural solutions.

Our team believes that it is vital that new agricultural technologies are both relevant and robust, build on well described initial design goals created from a strong understanding of the needs of farmers and their operations. If that is not done, then there will be delays in the development of the product and eventually quality, which will have ongoing negative effects on the trust of farmers in the product. Short testing cycles compound that problem, so the data used to design and build the systems needs to be of very high quality.

Our offer
Agri-EPI offers a wide-ranging set of facilities, equipment, and services. Our farm network is a key part of this, enabling the testing spaces and long-term interaction with farmers which we rely upon. Within the engineering team, we support the farm network and projects through our data engineering, data analysis and robotics specialisms.

Key resources include:

  • Multi-modal agricultural data
  • Spectral imaging and sensing
  • Agricultural data analysis
  • System simulation
  • Development / Robotic platforms
  • Data and robotics in agriculture consulting

Find out more here:

Engineering R&D brochure

Precision farmer explores innovation in viticulture

Ian Beecher-Jones, co-owner of JoJo’s Vineyard in Oxfordshire, has been a precision farming adviser for several years and is part of Agri-EPI Centre’s innovation farm network. At JoJo’s Vineyard, he is growing 6 different varieties of grapes to make still and sparkling wine and incorporates agri-tech at every level possible to enhance efficiency, sustainability and productivity.

JoJo’s vineyard is situated in the Chiltern Hills, near Henley on Thames, Oxfordshire. At the vineyard, Ian utilises the latest technology from drones, robots, satellites and data, which helps the team at JoJo’s make the best grapes possible.

There are many great traditions in vine growing that shouldn’t be lost. Ian explains that blending in new technology alongside the traditions will create an opportunity for vineyards in the UK to produce a product suited for the next new world in a sustainable way.

Ian said:

“We’re excited to be working with Agri-EPI to explore the opportunities for JoJo’s and the rest of the UK vineyards. The UK viticulture sector is on an incredibly upward journey, but we have to be aware of producing wine in the most efficient and sustainable way.”

Ian, in collaboration with Agri-EPI and robotics technology company, Antobot, has recently embarked on two projects at JoJo’s vineyard, one to create a vineyard digital infrastructure map, and the other for on-the-ground monitoring using the Antobot robot.

The mapping tool, developed with the Collabriculture project in South Australia, aims to create a shareable, digital infrastructure map of the vineyard’s rows and boundaries. The map can then be shared with any ag tech companies wishing to work with vineyards around the world. The model is the foundation on which drones, robots and vehicles can plan navigation paths before arriving on site, avoiding time wastage from surveying. This will improve the efficiency of data gathering services on farm.

Ian has described it as a contextualisation map as it gives context to all the other digital data maps that are generated on the vineyard.

“If I can’t overlay my rows and blocks on the satellite, drone or robot generated maps I get back, I can’t identify exactly where the variation is.”

“It is the share-ability of the digital infrastructure that is key to establishing a reliable and trustworthy data platform we can all work from. Once established we can share it with a range of ag-tech companies who see the benefits and opportunities of working with one of the fastest growing crops sectors in the country.”

“The exciting aspect about this project is the global potential to remove cost for growers and speed up the time it takes to engage with ag-technology companies whether they are providing drone, robot, satellite or software services. We are all working from the same infrastructure data.”

Vineyards are an ideal environment to work in since the pathways between the rows create a roadway for robots to travel. The robots are fitted with high level GPS and LIDAR systems to help them navigate around the vineyard.

The robots at JoJo’s will carry cameras and sensing equipment to monitor and analyse the vines and grapes as they grow during the year. Gathering data is a time consuming task. Robots and drones will speed that up.

 

Read more:

Case study

Live grain robot demo success on farm in the South West

On Tuesday 14th March Agri-EPI hosted a live demonstration of the Crover grain monitoring robotic solution at Manor Farms, Stratton-on-the-Fosse, kindly hosted by Jeremy Padfield and Rob Addicott who farm in partnership together.

They are both tenants of the Duchy of Cornwall and have been a LEAF Demonstration Farm since 2006 and members of the Agri-EPI Innovation Farm network since 2017. Working together as neighbouring farmers has brought many benefits to Rob and Jeremy such as shared machinery and investment costs. It has also allowed them to take up a number of precision farming techniques to help their businesses become more sustainable, such as engaging in the Crover project.

Crover’s first-of-its-kind grain monitoring robotic solution allows for a greater understanding of the real situation of grains stored in bulk, thanks to its patented method for locomotion through bulk solids, enabling grain storage operators to implement accurate Integrated Pest Management (IPM) practices to maintain the quality of their stock. The CROVER robot is the world’s first ‘underground drone’ in the sense of the first device able to propel itself below the surface of dense granular media such as sand, grains and powders.

It was a very successful event with great feedback and engagement from the guests and the demonstration in the grain shed went smoothly.

International Day of Mathematics

Happy International Day of Mathematics! Mathematics plays a significant role in agricultural technology in several ways:

  1. Modeling crop growth: Mathematical models are used to simulate the growth of crops. These models use mathematical equations to represent the different factors that affect crop growth, such as temperature, rainfall, soil nutrients, and pests. By using these models, farmers can predict how their crops will grow under different conditions and make informed decisions about when to plant, irrigate, fertilise, and harvest.
  2. Precision agriculture: In precision agriculture, farmers use technology to apply inputs (such as water, fertiliser, and pesticides) precisely where they are needed. This technique relies heavily on mathematical models, data analytics, and sensors to measure and monitor different parameters, such as soil moisture, nutrient levels, and pest populations.
  3. Farm management: Farmers need to keep track of a lot of data, such as crop yields, soil characteristics, weather patterns, and market prices. Mathematical tools help them organise and analyse this data, make predictions, and optimise their operations.
  4. Genetics and breeding: Mathematics is also used in genetics and breeding to study the inheritance of traits and develop new varieties of crops that are more productive, disease-resistant, and climate-tolerant. Mathematical models can help researchers identify the genes that control these traits, predict the outcomes of different breeding strategies, and optimise the selection of new varieties.

Overall, mathematics is an essential tool in agricultural technology, helping farmers and researchers make informed decisions and optimise their operations to meet the growing demand for food in a sustainable way.

Over the last months Agri-EPI has invested in the expansion of its team focused on data, engineering, and math, bringing on several new members and enabling them to offer a set of services to assist in the creation of agri-tech products.

Eliot Dixon, Head of Engineering, said:

“The team of platform and spectral imaging experts uses our fleet of sensors and specialist software to deliver a range of sensing products such as ground truthing for AI model generation, or the creation of digital twins. We are also now able to offer UAV and UGV platforms as a means to test novel sensors and end-effectors without the need for a bespoke vehicle. And through working closely with our innovation farm network, we are creating a heavily layered source of evidence for developers using our farm network to design and test their innovations.”

Agri-EPI’s GIS Data Analyst, Yingwang Gao, majored in Agricultural Engineering, and has a PhD degree specialising in Hyperspectral Imaging Applications, as well as postdoc experience working as Research Associate. In addition to a strong academic background, he has accumulated several years of industrial work experience, mainly on spectral imaging systems, R&D, and spectral imaging data analysis in various application domains. He has a strong passion for remote sensing and photogrammetry. At Agri-EPI, he takes care of data acquisition and data processing from different types of sensors, including RGB, multispectral, hyperspectral, LiDAR, and GPR, to identify and map out features of interest in the agricultural sector, to help farmers with better decision-making in agricultural management.

Agri-EPI’s new R&D Equipment Technician, Aditya Jadhav, pursued his bachelors in aeronautical engineering, where he learned various aspects of flying machines. He set up an aeromodelling club with a few of his classmates where they designed, built and tested various configurations of small UAVs. The MSc program for Autonomous vehicle dynamics and control was structured for students to gain a deeper understanding of unmanned systems. Aditya was part of a group project that built a surveillance system with a swarm of autonomous drones, and an individual project sponsored by the Railway Safety and Standards Board which aimed to design and develop an autonomous vehicle which can operate in a station environment. The advancements in robotics and the urgent need of integrating robotics with sustainable agriculture were the driving forces for him deciding to work in the agri-tech sector. As the R&D Equipment Technician, Aditya looks after all the deployable assets that are in service to the company, which includes maintenance, asset tracking and deployment, and organising the logistics.

Panagis Tzivras, Agri-EPI’S GIS Software Engineer, is a GIS expert with strong technical skills who is highly invested in programming. In his previous roles working with startups and the commercial sector, he was involved in data collection and extraction, maintaining data pipelines and building geospatial processes and automation updates. At Agri-EPI Centre he is helping to leverage the measurement resources of the centre to create high quality dataset and support systems. He is working on creating tools and code to enable the automation of data collection from a wide variety of sources available to Agri-EPI Centre.

Lastly, Aidan Robertson has joined the Agri-EPI Engineering team as their new Graduate Data Analyst. Aidan’s background is in mathematics, which he studied at University of Warwick for four years before looking for jobs related to data science. He has been working on projects related to the health and wellbeing of cows, specifically by reformatting farm datasets to be sent out for analysis. Soon, there are plans for him to begin a more ambitious project to develop a costings estimator for RAS in agriculture. This is a long-term task, but the ultimate goal would be to offer it as a service for farmers looking to introduce robotic systems into their farms. The most interesting part of agri-tech for Aidan is the data, and what it actually says about the performance of a system, as well as what can be done to help the problems being faced by the agri-tech sector at present.

 

 

Collaboration essential for successful agri-robotics

By: Eliot Dixon, Head of Engineering at Agri-EPI Centre

Robotics has several strong applications in agriculture, especially in scenarios where systems can enhance the productivity of a shrinking workforce or can offer production efficiencies to the farm. However, to be successful in these applications the systems created need be reliable, in terms of long-term physical robustness but also in the ability of their control software to handle the very wide variety of scenarios they will encounter in a farming environment. This means the robots must be both well designed and well tested to meet the needs of farmers. This includes a design which emphasises safety and reliability.

“Understanding user requirements and testing in-field is key”

Good design requires a deep understanding of the needs and requirements of farmers and their farming systems. This extends from the core values held by a farmer, such as safety, which dictate their decisions; through to very specific requirements created by the unique combination of their way of working and the land they work. If this understanding is not achieved for a farming system, then there is a very high chance that the eventual product will be unsuitable, either creating a failed product or a long development timeline to solve the deficiencies. Gaining this understanding should come through working with a wide variety of farms within the target market for the technology, not just a small handful. In many agricultural sectors this design stage is especially important due to the limited testing season and ability to iterate on the design.

Testing is also well understood to be important to creating a reliable product, and in agriculture this does require a close collaboration with farmers to ensure that the robot meets their needs. As these are complex machines, which are also often dangerous if not created with a strong safety process, the testing regime should also be rigorous enough to ensure that the system will function to the desired reliability for all the design requirements. A rigorous testing regime would usually require multiple tests for each requirement across multiple operational scenarios such as different weather conditions, soil types, dangers, failure modes, crops etc. Failure to complete this testing will certainly result in the robotic system encountering situations which it is unable to function within, which may create unfortunate repercussions for the user or manufacturer. Unfortunately, completing this massive number of tests requires a range of test facilities, some of which might be beyond the capability of a company focussing on a small range of agricultural applications.

In our 2021 hackathon we explore safety and security. Outcomes are discussed in our white paper here:

Hackathon white paper

As mentioned, good design and testing is essential to creating successful products, but this unfortunately comes with a high cost. Doing this for the wide range of complex operating scenarios in UK agriculture, as well as the short testing cycles, is driving up the cost of developing agricultural robots. There are a multitude of Agri-robotics companies in the UK creating their systems from almost the ground up, each of which are individually bearing the cost in time and money of this development. This creates barriers to adoption in terms of high costs, a limited set of operations which can be conducted by robots, or low reliability due to poor engineering, and is increasing the amount of time it takes for products to get to market. As in all development the saying “Good, Cheap, Fast. Pick two”, is very much in action here but some very pressing needs mean we must find ways to break that deadlock.

Collaboration enables future opportunities for robotic systems

The obvious solution for this deadlock is to massively increase collaboration between ag-robotics developers. This has been proposed for many years, but we are yet to see a viable solution to this. Direct collaboration is currently difficult for commercial reasons with developers competing for the same money, but also for technical reasons where it is challenging to share components between robots. Perhaps a solution for this is to build an ecosystem of adaptable, compatible, components and platforms which can be used to create a multitude of agricultural robotic systems. This ecosystem of components would also be able to be robustly tested to ensure reliability when integrated as part of a larger system. Thus, the costs of development would be increasingly shared, without any single robotics manufacturer losing income as they are all developing for specific agricultural niches. Using a set of well proven components would allow developers to focus on ensuring good understanding and design for specific problems in agriculture, while also allowing for easier integration and testing of the robots.

Robotics in agriculture is a promising field, and with the right design and testing, as well as collaboration between developers, it could be a great success. By understanding the needs and requirements of farmers and using that to create an ecosystem of components and platforms, robots can be developed which are high value, robust, reliable and safe. With the right approach, agricultural robotics could benefit farmers across the UK and worldwide. Read our robotics and automation article to understand more about how we can support you to develop a robust well tested solution through collaborative R&D today.