Category Archives: Automation

AgTech, Automation, Conference, Research

Refill Scheduling for Agricultural Robots and Other Vehicles

Rob Fitch

Refill scheduling is the problem of deciding when a robot or other agricultural vehicle should pause in its work to replenish a resource, such as herbicide or fuel. This problem is commonly solved in broadcast spraying, for example, by simply running the spray tank dry and then refilling it.

This strategy actually leads to lost time in traveling to the refill location, and we can show that these time losses can be significant. When multiple machines must queue at a refill location, the problem is made worse.

In this talk, Rob will explain the theoretical difficulty of this problem and give examples from robotic spot-spraying and broadcast spraying to illustrate the potential time losses. He will present an optimisation approach that chooses optimal refill times to minimise travel distance and queuing time. These results apply to agricultural robots, human-driven spray rigs, and any other machine that must refill or empty some material at a fixed location during the course of its work.

Rob will conclude the talk by tying these results into the larger research program in agricultural robotics, including novel machine learning methods for fruit/vegetable detection that support selective harvesting.

Rob Fitch is Associate Professor at University of Technology Sydney.He was previously a Senior Research Fellow with the Australian Centre for Field Robotics (ACFR) at The University of Sydney where he retains an honorary position. He is a leading research scientist in the area of autonomous field robotics. He is interested in systems of outdoor robots and their application to key problems in agriculture and environmental monitoring.

Robert received his PhD in computer science from Dartmouth (USA). He has led research in planning and collaborative decision-making for both ground and aerial robots in a variety of government and industry sponsored projects including those in broad-acre agriculture, horticulture, bird tracking, and commercial aviation.

 

AgTech, Automation, Conference, Data Analytics

Integrating Public and Private Spatially-based Data

Aaron McCallion

Very pleased to confirm Aaron McCallion as a speaker at our Annual AgTech Conference LandWISE 2017: Are we ready for automation?

Aaron’s presentation will focus on how public and private data are being integrated to provide better land management outcomes.

For example, a recent European initiative has used data integration to automate pesticide application to crops in a way that protects adjacent natural ecosystems through the use of legal buffer zones identifiable by machine readable maps. 

In New Zealand, integration of public and private data is being piloted to assist Maori land owners in achieving economic returns within their environmental, social and cultural values.  This is being enabled through open government data initiatives that include legal land titles, vegetation cover maps, soil databases, digital elevation models and remote sensing.

The impact of different land management approaches can be assessed when such public data is combined with private data that includes historic land use practices, climate monitoring, ecosystem health indicators, inputs and financial data.

Visual representation of this spatial data in interactive mapping and analysis tools can then allow users to understand land management issues as well as aid the identification of risk mitigation or restorative strategies.  

Aaron will discuss what is needed for such approaches to be effective,  and ethical and legal requirements that need to be maintained with respect to privacy where the public or private data could identify individuals.

Aaron McCallion is Executive Director of Waka Digital, a leading Information Technology firm established in 2006 to deliver IT and communications based products and services. 

Aaron combines system dynamics modelling, economics and management with his understanding of sustainable development and environmental restoration. His skills include assessment of effectiveness, efficiency, user satisfaction and accessibility to measure or improve the usability of new or existing products or services, including prototypes.

He is a Key Researcher in the MBIE programme, Oranga Taiao, Oranga Tangāta – Knowledge and Toolsets to Support Co-Management of Estuaries and previously in the MBIE gold-rated programme, Manaaki Taha Moana-Enhancing Coastal Ecosystems for Iwi. (2009-2015)

Aaron has a BBS from Massey University and an M.B.A. through the global program operated jointly by Sejong University in Korea and Syracuse University in the United States.

AgTech, Automation, LandWISE People, Precision Agriculture, Research, Sensing

In Search of Farm Robots: Ch 1

A version of this article previously appeared in The Grower

Dan Bloomer has been travelling in Australia and Europe asking, “How ready are robots for farmers and how ready are farmers for robots?”

Notable areas of active research and development globally are scouting, weeding and fruit picking.  Success requires machines that can determine and follow a route traversing whatever terrain it must, capture information, identify and selectively remove weeds, and identify, pick and transport fruit.  They have to sense, analyse, plan and act.

Robotics is widespread in industries such as car manufacturing that have the exactly the same task being repeated over and over again. With possible exception of robotic milking, farm operations are not like that. Virtually every single case is unique with unique responses needed.

Many groups around the world are looking at robotic weeding . There are many items needing attention. How do we tell weeds from crop plants? Can we do that fast enough and reliably enough to make a robot commercially viable on-farm? Once identified, how do we optimise robotic arm movement to best attack a patch of weeds?

The Australian Centre for Field Robotics (ACFR) at the University of Sydney is well known for its field robots such as the solar powered Ladybird. The new generation Ladybird is known as Rippa, and is currently undergoing endurance testing. Look on YouTube for ACFR videos and you’ll even see SwagBot moving around rolling hill country.

A key theme for Rob Fitch and colleagues is Active Perception: perception being what we can detect with what accuracy and confidence; active meaning in real time and including planning actions. They invest heavily in developing mathematics to get fast results. And they are succeeding.

Using Intel’s RealSense structured light camera it takes them less than half a second to identify and precisely locate groups of apples on a trellis. Within that time they also calculate exactly where to place the camera to get a second confirming view.

Smart maths allow ACFR scientists to capture 3D images and identify and locate apples in less than half a second
Smart maths allow ACFR scientists to capture 3D images and identify and locate apples in less than half a second

Cheryl McCarthy and colleagues at the National Centre for Engineering in Agriculture (NCEA) are conducting a range of research projects that integrate autonomous sensing and control with on-farm operations to robotically manage inputs within a crop. Major projects include automation for weed spot spraying, adaptive control for irrigation optimisation, and remote crop surveillance using cameras and remotely piloted aircraft.

At LandWISE 2015, Cheryl reported on their machine vision and sensing system for weed detection systems that uses depth and colour segmentation and a new processing technique to operate at commercial ground speeds of 10-15 km/h.

Now Cheryl is using UAVs to capture photos of crops, stitching the pictures to get a whole paddock image, then splitting it up again to efficiently identify and locate individual plants and weeds. This is enabling her to create accurate maps some other weed destroying robot can use.

cherylmccarthy
Research at the University of Southern Queensland investigates UAVs to scout paddocks combined with image stitching and analysis for interpretation to create maps of weeds for later treatment

SwarmFarm founders, Andrew and Jocie Bate grow cereals and pulses near Emerald. Spray-fallow is used to conserve water in this dryland environment and WeedSeeker® and Weedit® technologies reduce chemical use to a very small percentage of traditional broadcast application.

4WD SwarmFarm robots carrying WeedSeeker technology cover the paddock spraying only living weeds
4WD SwarmFarm robots carrying WeedSeeker technology cover the paddock spraying only living weeds

With large areas, most growers move to bigger machinery to maximise labour efficiency. This has a number of adverse effects including significant soil damage and inability to work small areas or work efficiently around obstacles such as trees.

SwarmFarm chose robots as practical light weight equipment. They reason that several small machines working together reduce soil impact and have the same work rate as one big machine. Andrew estimates that adoption of 8 m booms versus 34 m booms could increase the effective croppable area in Queensland by 2%.

Are these robots ready for farmers? Are farmers ready for these robots?

Only SwarmFarm has multiple machines currently working on farm in Australia. They are finalising a user interface that will allow non-graduate engineers (smart farmers) to manage the machines.

The question that remains is, “Why would I buy a specialised machine when I can put a driver on a cheaper conventional tractor or higher work rate sprayer and achieve the same?”

Is it the same?

Travel to Australia was supported by a Trimble Foundation Study Grant

AgTech, Automation, LandWISE People, Precision Agriculture, Research, Sensing, Soil, Tillage

In Search of Farm Robots: Ch3 Switzerland, France and England

This article originally appeared in “The Grower”

A desire to reduce soil compaction and avoid high and inefficient use of chemicals and energy inspired Steve Tanner and Aurelien Demaurex to found eco-Robotix in Switzerland.

Their solution is a light-weight fully solar-powered weeding robot, a 2 wheel drive machine with 2D camera vision and basic GPS. Two robotic arms position herbicide nozzles or a mechanical device for precision weed control.

Steve Tanner lab testing the exoRobotix vision and robotic weed control system

The ecoRobotix design philosophy is simplicity and value: avoiding batteries cuts weight, technology requirements and slashes capital costs. It is a step towards their vision of cheap autonomous machines swarming around the farm.

 Bought by small farms, Naio Technologies’ Oz440 is a small French robot designed to mechanically weed between rows. The robots are left weeding while the farmer spends time on other jobs or serving customers. Larger machines for vegetable cropping and viticulture are in development.

Prototypes V1, V2 and V3; precursors to the Naio Oz440 show the steps in a robot’s development

Naio co-founder Gaetan Severac notes Oz440 has no GPS, relying instead on cameras and LiDAR range finders to identify rows and navigate. These are small machines with a total price similar to a conventional agricultural RTK-GPS system, so alternatives are essential. 

Tech companies have responded and several “RTK-GPS” systems are now available under $US1000. Their accuracy and reliability is not known!

Thorvald an example of research collaboration: Norwegian University robot being automated at University of Lincoln show the common design of four wheel steer and four wheel drive

Broccoli is one of the world’s largest vegetable crops and is almost entirely manually harvested, which is costly. Leader Tom Duckett says robotic equipment being developed at the University of Lincoln in England is as good as human pickers at detecting broccoli heads of the right size, especially if the robot can pick through the night.  With identification in hand, development is now on mechanical cutting and collecting.

In 1996, Tillett and Hague Technologies demonstrated an autonomous roving machine selectively spraying individual cabbages.  Having done that, they determined that tractors were effective and concentrated on automating implements. They are experts in vision systems and integration with row and plant identification and machinery actuation, technology embedded in Garford row crop equipment. 

Parrish Farms has their own project adapting a Garford mechanical to strip spray between onion rows. Nick Parrish explained that Black Grass control was difficult, and as available graminicides strip wax off onions boom spraying prevents use of other products for up to two weeks.

Simon Blackmore is a global leader in farm robotics thinking at Harper Adams University. His effort to address robotic safety issues includes a seven level system:

  1. Route planning to avoid hazards and known obstacles
  2. Laser range finder to sense objects and define them as obstacles
  3. Wide area safety curtain sensing ground objects at 2m
  4. Dead man’s handle possibly via smartphone
  5. Collapsible bumper as a physical soft barrier that activates Stop
  6. Big Red Buttons anyone close can see and use to stop the machine
  7. Machines that are small, slow and light minimise inertia

“Hands free hectare” is Harper Adams University’s attempt to grow a commercial crop using open source software and commercially available equipment in an area no-one enters.

Harper Adams research to develop a robotic strawberry harvester is notable for the integration of genetics for varieties with long stalks, a growing system that has plants off the ground, and the robotic technologies to identify, locate and assess the ripeness of individual berries and pick them touching only the peduncle (stalk).

So what have I learned about farm robotics?

  • People believe our food production systems have to change
  • Farm labour is in short supply throughout the western world
  • Machines can’t get bigger as the soil can’t support that
  • Robotics has huge potential but when
  • Safety is a key issue but manageable
  • There is huge investment in research at universities, but also in industry
  • It’s about rethinking the whole system not replacing the driver
  • There are many technologies available, but probably not the mix you want for your application.

As Simon Pearson at the National Centre for Food Manufacturing says, “It’s a Frankenstein thing, this agrobotics. There are all sorts of great bits available but you have to seek them out and stitch them together yourself to make the creature you want.”

Dan’s travel was supported by a Trimble Foundation Study Grant

AgTech, Automation, LandWISE People, Precision Agriculture

NZ AgTech meets Silicon Valley

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This article previously appeared in The Grower

You can read about things, but actually experiencing them is something else.

Dan Bloomer joined Callaghan Innovation , NZTE and two dozen New Zealand agricultural technology organisations for a week in San Francisco.

The purpose was to understand how New Zealand could fit with the US agricultural technology scene. We visited UC Davis, agricultural technology companies, Silicon Valley start-ups and venture capital firms.  We visited an almond orchard, a vineyard and a winery in Napa Valley. We went to a large raspberry farm in Salinas.

Driscoll’s berry fruit operation highlighted the difference in scale between New Zealand and the USA. With $US 3 billion in annual sales and a global growing and sales network, they have an advanced and comprehensive R&D programme.

The issues facing Driscoll’s are fully familiar to any farmer in New Zealand: produce more from less, reduce wastage all along the supply chain, prevent nutrient loss to water, address the disappearing labour force, meet increasing regulatory requirements, prove provenance and food safety, and get the best product to the right market in excellent condition at an acceptable price.

While at Driscoll’s we heard from technology companies with whom they are collaborating to address issues facing them now and in the future.

AgroBot is a machine developed by a Spanish entrepreneur to automate picking small produce like strawberries.

HarvestPort provides an on-line connection to share seasonally used resources such as fruit bins or crates.

Growcentia is developing microbial biostimulants to increase crop production and decrease the environmental impact of agriculture.

GeoVisual is focused on remote sensing and big data analytics to improve and predict crop yields, better manage croplands and improve harvests.

Food Origins is focused on precision data collection and analytic services for hand harvested produce.

Each of these could add value in New Zealand.

AgTech is growing very fast. Wharf42 reported that 499 companies attracted US $4.6 billion of venture capital investment in 2015, nearly doubling 2014 figures. 303 companies were in the US. India came second with 64 and Australia 11th with 6 investments.  Although we have some local investment, New Zealand didn’t register on the global stage.

In New Zealand we are impressed by million dollar investments. Climate Corporation was bought by Monsanto for $US 1 billion. It aims “to build a digitized world where every farmer is able to optimize and flawlessly execute every decision on the farm”.  Yamaha just bought a share in UAV company PrecisionHawk in a $US 18 million deal.

We spoke with venture capital firms about accessing funding. Swamped by opportunities within two hours of the San Francisco CBD, they have no need of New Zealand. So New Zealand needs to have excellent technology, travel to them and have obvious local presence.

The week of intense stimulation, new experiences and gaining new understandings left me very positive about New Zealand technology capability and about our prospects in the world agtech markets.

We have numerous New Zealand companies that easily compete on a technology level with what we saw.  We can do it, and with Callaghan Innovation , NZTE and private initiatives, there are things in place to help New Zealand companies succeed in this enormous market. But we have to think differently and execute very well.

When the right technology gets presented in the right way in the right place things can happen very fast. After winning a major US innovation award for its noise-reducing drone technology, nine month old New Zealand startup Dotterel Technologies is on a fast track to global success. We need more Dotterels.

This visit was organised by Wharf42, NZTE, Callaghan Innovation and the Silicon Valley Forum.

Agronomy, AgTech, Automation, Irrigation, MicroFarm, Nutrients, Plant Health, Precision Agriculture, Projects, Research, Sensing, Soil

Onion Crop Research Plan

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After identifying areas within paddocks that had yields limited by different probably causes, we conceived the idea of Management Action Zones (MAZs).

Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both
Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both

Some areas showed that yield was limited by plant number: establishment was poor. Others had the expected population, but low biomass: the plants were small due to some other limiting factor.

If we can identify zones easily, and determine the causes, we should be able to target a management response accordingly. So for this season, we set out a revised research aim.

What we want to know:

  • Can we successfully determine a management action zone in a field?

Why do we need to know this?

  • Develop a tool to increase uniformity and yield outcomes
  • Develop a tool to evaluate management practices and crop productivity

If we want to successfully determine a management action zone in a field then there are two main steps to achieve in this year’s work:

  • Confirm the relationship between digital data and crop model parameters
    • Does the relationship stay constant over time and sites?
    • How early in growth can a difference be detected?
    • Can the relationship be used to show a growth map across a field?
  • Develop an approach to gather information and ways to input and display results, initially using a website approach.
    • Can we integrate a plant count and yield information to start developing a management action zone?
    • How should this be put together in a way growers can start to use to gather information about their crops?

At the MicroFarm, we established six research zones based on paddock history and excessive wetness at establishment.

We have three paddock histories: two years of onion production with autumn cover crops of Caliente mustard, two years of onion production with autumn cover crops of oats, and no previous onion crops planted after previous summer sweetcorn and autumn sown rye grass. In each of these areas, we deliberately created sub-zones  by applying about 45mm of spray irrigation as a “large rain event”.

Artificial heavy rain event applied after planting and before emergence
Artificial heavy rain event applied after planting and before emergence

The impact of the artificial rainstorm is evident on images taken at the end of November.

The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
AgTech, Automation, Irrigation, Nutrients, Precision Agriculture, Sensing, Soil, Water

Technology to Reduce N Leaching

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N-Leach_WorkshopThe Precision Agriculture Association NZ is presenting workshops focused on technologies available to help reduce nitrogen leaching. There are two North Island workshops being offered at:

Massey University on Thursday 1st September 2016 [PDF here]

and

Ellwood Centre, Hastings on Friday 2nd September 2016 [PDF here]

Programme

The ‘Technology to Reduce N Leaching’ workshops are similar to the well received program conducted in Ashburton in March 2016 and will address where we are and what we can do about nitrate leaching limits in a North Island context utilising a range of technologies and farm systems options.

The particular areas for focus for the program are:

  • Variable rate technologies and systems
  • Precision irrigation
  • Precision spreading systems and services
  • Soil mapping
  • Soil moisture monitoring, sensors, metering
  • Nutrient budgeting and environmental monitoring

A Q & A time slot is devoted in the afternoon session for attendees to interact with members and presenters on the day to share learnings and understandings about the issues. This will also be possible over the lunch break on both days with one and half hours devoted for this.

PAANZ2

Offer to PAANZ Members

As part of the Hastings program only on 2nd September, PAANZ members are offered the opportunity to participate as trade/sector participants for technologies and products as may be appropriate to support the program.

PAANZ is not able to offer trade/sector stand space at the Palmerston North venue due to space restrictions unfortunately so only the Hastings venue will be able to accommodate this option for members.

If you would like to participate please advise Jim Grennell, E-mail: jim@paanz.co.nz

Mobile: 021 330 626, places are limited to ten organisations for the Hastings workshop to be involved as a trade/sector participant so it will be on a first come basis.

The cost of participation will be $100.00 plus GST per stand with attendance fee of $100.00 per person additional.

As these are indoors Workshops, with a technology focus and space at the Hastings venue is limited no large equipment or hardware can be accommodated.

Confirmation of members wishing to take up this opportunity is required by Monday 22nd August 2016 after which time the opportunity to participate will be made available to non-members.

AgTech, Automation, Precision Agriculture

Digital Agriculture – Challenges and Risks

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Associated Technologies Including Robotics

TristanPerez1

 

Tristan Perez, Queensland University of Technology

 

There is big hype at the moment about big data, big-data analytics, machine learning, artificial intelligence, and robotics. Some of these terms are starting to make it into agriculture, especially when we consider the potential impact of data flows from an integrated value chain.

There is little doubt that the judicious application of some of these concepts and associated technologies will be transformational to the agricultural industry. However, there are also some risks.

In this talk, I  attempted to define some of the terms above using simple examples within the agricultural context and discuss how the associated technologies including robotics could be applied.

I  also highlighted the challenges and risks associated with generating and using data without appropriate regard for the underlying management problems we seek to address.

AgTech, Automation, Planting, Research

Weeding Robots: A Global Review

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Current Prototypes of Field Robots

Armin Werner1 Rory Roten1 Luc van Rijen2
1 Lincoln Agritech PO Box 69 133, Lincoln 7640, New Zealand
2 HAS University of Applied Sciences, The Netherlands
Email: Armin.Werner@lincolnagritech.co.nz

Excitement is being generated at conferences, farmer’s workshops and the general media about the next level in precision agriculture: field robots. We all know that robots work in factories to carry parts or conduct specific actions in manufacturing and that indoor robots are already standard technology in many industries.

There is also interest in developing autonomous equivalents in agriculture beyond the current tractor-carried or self-propelled equipment. There are already some tomato and cucumber picking robots in use in greenhouses in Europe and North America. However, stepping out of the ‘controlled’ environment of a factory building or a greenhouse into the unforgiving conditions of an arable field, a pasture or an orchard poses many serious challenges for scientists and engineers.

Most of these technical challenges have been solved or at least solutions are prototyped for outdoor conditions. This includes the exact positioning and the orientation of the robot under changing ambient light and weather or infrastructure, the recognition of the dynamically changing environment of a field robot as well as precisely controlling the actions that a robot has to conduct in a highly variable environment.

With these preconditions in mind, it is most likely that agricultural robotics will develop very fast in the next years. It is unclear what the first major applications may be and what challenges farmers will face when it comes to using such robots as standard equipment. From discussions with farmers, growers and the industry it is anticipated that weeding robots for row crops (annual field crops, perennial tree and vine crops) will be a good candidate to pave the way for field robots into agriculture.

The presentation will give an overview of current prototypes and weeding robots which are commercially available. We will discuss general differences between these robots and the type of applications that are intended.

Automation, Drainage, Research, Sensing

A Digital Horticulture Research Strategy

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Value Chain Approach To Identifying Priorities

Roger Williams

Roger Williams
New Zealand Institute for Plant & Food Research Limited (PFR)

 

The industrial revolution gave us machines and agri-inputs that enabled us to farm at scale and speed. The green revolution began to unlock the potential of plant genes to increase yield. Now the digital revolution provides us with an opportunity to harness the power of ‘big data’ and technological innovation to radically re-engineer our horticultural production methods and supply chains.

Digitally informed decisions during production, harvesting, sorting, packing, storage and transit could be the basis for a step change to high profitability, high resource efficiency and low footprint horticultural value chains.

Identifying the research priorities that we need to realise this opportunity in New Zealand is a challenge in itself, given the pace of developments in sensing technology, robotics and the internet of things globally. Accordingly, Plant & Food Research assembled an expert panel from across its science teams, augmented with other specialists from New Zealand and Australia, to develop a digital horticulture research strategy.

The panel has taken a value chain approach to identifying research priorities, particularly in relation to production, harvesting, sorting and packaging, storage and transit.  Future science needs are structured around the concepts of ‘sense, think, act’ for each part of the value chain and are linked by an ‘artery’ of data to feed forwards and backwards along the value chain.

Plant & Food Research looks forward to working with a wide range of partners to deliver this digital horticulture strategy for the benefit of New Zealand’s producers and exporters.