Bringing more efficiency to the farm

Automation for Agriculture: Bringing more efficiency to the farmAUGUST 2020

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August 2019 Mechanical Engineering Magazine Special Report 2

Introduction

Automation—and especially digitally driven automation—has revolutionized

industries from transportation to manufacturing. Increasingly, agriculture

is being automated as well. Different segments of the agriculture industry are

approaching automation in different ways—but at farms large and small, it is

changing traditional practices and processes. And, today, everything from ro-

botics to sensors, drones, autonomous vehicles,

GPS, and machine learning are finding their way

into new generations of farm equipment.

“There are so many areas of technology

coming together in agriculture. We’ve got more

technology in our pockets now than what they

had to send the first missions to the Moon,” says Luke Zerby, North America

brand marketing manager for New Holland, the global farm equipment manu-

facturer. “It’s a matter of how do we use those for the farmer?”

Universities, large manufacturers, and variety of startups are working on

that question—and coming up with a range of innovative answers that prom-

ise to make farming more efficient, productive, and sustainable.

“There are so many areas of technology coming together in agriculture. It’s a matter of how do we use those for the farmer?”


Growing Demand, Troubled Supply

The interest in agricultural automation is growing for several reasons. In

the coming decades, the world will have a far greater number of people

to feed. With factors such as climate change and water scarcity, “groups like

the UN project that we could have food shortages approaching 70 percent in

a few decades if we don’t act,” says David Slaughter, professor of Biological

and Agricultural Engineering at the University of California-Davis and leader

of the university’s Smart Farm initiative. “The cli-

mate-change models show that the yields of crops

in California, for example, could decrease by 15

percent.”

At the same time, the agriculture industry strug-

gles to find enough people to grow that food. The

industry is experiencing an ongoing global labor

shortage that is driven by everything from urban-

ization and immigration policy to the aging of many rural populations. In a

recent California Farm Bureau survey, 56 percent of farmers said that over the

past five years they had been unable to obtain all the workers they needed to

produce their main crop. And a decade ago, researchers at Washington State

University (WSU) were working on a robotic asparagus harvester when the

market suddenly shifted.

“When you move that outdoors—with varying weather conditions, the soil under the wheels changing, and the crops growing—you have a lot of layers of complexity that you have to overcome.”


“The asparagus planting area in the state of Washington was reduced by

90 percent over a short period of time,” says Qin Zhang, a WSU professor

and director of the university’s Center for Precision and Automated Agricultur-

al Systems. “The industry could not find sufficient labor to harvest asparagus,

so farmers decided to move to other crops in order to keep making a living.”

More automation promises to help address these challenges, but imple-

menting it is not always as straightforward as it is in other industries. “In

manufacturing facilities, you’ll see robots automatically haul chassis and

other parts around a plant. It’s a very controlled environment with a lot of

repetitive tasks,” says New Holland’s Zerby. “But when you move that out-

doors—with varying weather conditions, the soil under the wheels changing,

and the crops growing—you have a lot of layers of complexity that you have

to overcome.”

Nevertheless, the industry has made a great deal of progress in many ar-

eas. While automation in specialty crops such as fruits and vegetables is still

fairly limited, a great deal of automation has found its way into the manage-

ment of large row crops, such as corn and soybeans. Indeed, GPS systems

have been used for two decades to automatically guide large farm tractors

and other equipment. Operators input coordinates, and the machine takes

over to plow in straight lines and avoid gaps in seeding and spraying. But

those tractors still need to be supervised by a human sitting in the cab.


The Quest for More Autonomy

Now, the industry is taking things to the next level and bringing greater

autonomy to these farm machines. For example, manufacturer CNH

Industrial has produced autonomous tractor concept vehicles, including

NHDrive, which is based on of the company’s New Holland brand tractors.

“We had all this automation in tractors already, where 85 percent of the job

was handled automatically. So the NHDrive is really

just that next logical step,” says Zerby.

The NHDrive tractor has two RGB color cam-

eras in the front and two in the back, as well as

front-mounted radar and LiDAR sensors that detect

obstacles. It follows a path that can be set up by

an operator or automatically generated by the system’s software, based on

the size and shape of the field, the width of the implement being pulled, and

any fixed obstacles, such as poles or structures, that might be in the way.

As the tractor works, the operator can use a tablet or computer to remotely

monitor the cameras, access data about the tractor, and control settings for

engine speed, the implements being pulled, and so forth.

“If it senses an obstacle, it stops,” says Zerby. “With the cameras, the

Operating without a driver, the tractor can work around the clock to take advantage of good weather or harvest rapidly ripening crops.


operator can see what the problem is and send a command telling the tractor

what it should do.”

Operating without a driver, the tractor can work around the clock to take

advantage of good weather or harvest rapidly ripening crops. At the same

time, however, it has a full cab to accommodate a driver when necessary.

Farmers often have to use public roads to move from one field to another,

Zerby explains, and having a driver handle that task allows the farmer to

legally move the vehicle from field to field without having to trailer and haul it

by truck.

Raven Industries, the Sioux Falls, South Dakota, maker of precision farming

equipment, has taken a different approach. Dot, the company’s fully autono-

mous, diesel-powered platform, measures 20 ft. x 12.5 ft. and weighs 13,500

lbs. Dot navigates via GPS, and will soon incorporate additional sensors to

provide more information about the surrounding environment. Essentially a

U-shaped table, Dot is designed to carry a variety of implements, weighing

up to 35,000 lbs., that are built to be “Dot ready.” Currently, there are Dot-

ready implements from various vendors for seeding, spraying, and delivering

granulated fertilizer—and more are on the way.

“The implements mount on the platform, and it really becomes a self-con-

tained unit,” says John Preheim, director of engineering at Raven Industries.

“It’s a true autonomous platform, but it still requires supervision by someone

in the field.” The company expects that, in time, that supervision won’t be

necessary. Raven is also developing a system that will let one person operate

several machines at once, using a tablet.

Some autonomous vehicles are designed to work in concert with oth-

er equipment. Raven has developed a new system called AutoCart—a


GPS-guided driverless tractor that pulls a grain cart. The cart syncs up with

and moves automatically alongside a harvester as it is being driven down a

row and uses a camera to help track the harvester and detect objects in its

path. The harvester’s conveyor loads grain into the cart, and when that’s full,

the AutoCart automatically drives back to a station to be unloaded and then

returns to the harvester. With this approach, one driver can handle both the

harvester and the grain cart.

Most autonomous farm equipment is still fairly new and not yet in wide

use. However, Preheim says, “This is coming faster than the market initially

thought, and we believe that the tipping point with autonomy in agriculture

will come much more rapidly than in other industries, such as automotive.”

For one thing, autonomous driving in a farm field involves relatively few

regulatory and legal complications. What’s more, Raven and other companies

are offering kits that turn traditional tractors into autonomous vehicles—

something that is not likely to work well for highway vehicles. “We can begin

to automate the existing farm fleet,” says Preheim. “The farmer doesn’t have

to give up the capital investment they have already made. We think we’ll see

a smooth transition to having more autonomous machines on the farm. We

will see manned and unmanned machines in the field working together, and

then gradually, more of them will be unmanned, with the farmer controlling

more and more machines, from more remote locations.”


Small Robots Promise Big Change

Autonomous equipment is targeting a range of tasks on large row crop

farms, from planting to weeding and spraying. Some robots are also

helping the industry take advantage of data to improve operations. Earth-

Sense, a spinoff based on research at University of Illinois Urbana-Cham-

paign (UIUC), is using robotics to help breeders develop more resilient strains

of plants.

Traditionally, plant breeders have divided fields into grids of 3-meter square

plots and planted different seeds in each plot. They would then monitor

growth by periodically sending teams of people out into the field to assess

the plants. Typically, it is hard to find and train people for this work, and the

human assessments can be inconsistent, according to Girish Chowdhary,

professor of field robotics at UIUC, and co-founder of EarthSense.

EarthSense has created a small, four-wheel robot that is just 11 inches

wide, and designed to move between rows of crops such as corn at 1 mph.

Weighing about 15 lbs. and powered by four electric motors, it has two

LiDAR sensors—one facing forward for navigation and one facing upward to

gather information about plants. It also has a camera on each side and one

facing upward that also gather plant data. Connected to the cloud and using

machine learning, the robot combines information from these sensors and its

own forward movement to create a 3D map of each row and provide growers


with information about the number and heights of plants, stem width, density

of leaves, and other factors relating to plant health.

The robot is currently being used by a number of large agricultural

companies.

With the EarthSense robot, there is no need to find and train numerous

people for the job, and measurements are more consistent. In addition, it

works underneath the crop canopy, where drone and satellite imaging can’t

reach. EarthSense is now working on equipping the robot to spray or me-

chanically control for weeds, which it can do in a more targeted manner com-

pared to overhead spraying techniques, resulting in a reduction of chemical

use of 50 percent or more, depending on the

application, according to Chowdhary.

Chowdhary sees this robot as part of a

larger trend toward “decentralization,” which

has the potential to lead to new approaches

in agriculture. “You can decentralize the one

big tractor into many little ones that can be

distributed,” he says. The reason that has

been difficult in the past is “because you needed a babysitter for each of the

small machines.” But with autonomous robots, one operator could oversee

and coordinate many robots. With that in mind, a number of companies and

researchers are looking at “swarm” robotics for agriculture, where groups of

coordinated drones could map and monitor fields or a group of small robots

could cooperate to plant seed or weed fields.

With autonomous robots, one opera-tor can oversee and coordinate many robots. With that in mind, a number of companies and researchers are looking at “swarm” robotics for agriculture.


A decentralized approach has a number of potential benefits, says Chow-

dhary. For example, the technology is “scale neutral”—rather than buying one

large harvester, a farmer can easily match the number of small robots to the

task. “Small farmers are often not profitable because they don’t have enough

a scale to buy the big equipment. With these types of robots, if you have a

small farm, you might get just one, and if you have a huge farm, you could get

100,” he says.

Decentralization could also help farmers take advantage of different

crop-management strategies. For example, prior to a harvest, farmers some-

times plant cover crops to protect land after the main crop is harvested. But

with some crops, like corn, this is not practical.

“The big tractors cannot plant the cover crop without hurting the corn,

Chowdhary says. “But the smaller robots could provide a solution that would

let more farmers do that.”

Decentralization could also open the door to giving farmers more flexibility

in what they grow. Often, large farmers are essentially locked into growing

their specific row crops. Because of the specialized heavy equipment and

infrastructure investments involved, it is simply too expensive to switch. With

decentralized robots, however, equipment would be more flexible, making it

possible to turn to new crops when markets or climate conditions change.

Chowdhary also sees the possibility of diversifying by using small robots to

cost-effectively manage vegetable or fruit crops on the edges of large farms,

without having to find the labor to do so.


The Challenge of Specialty Crops

Managing specialty crops, such as fruits and vegetables, is especially

labor intensive, making the shortage of agricultural workers especial-

ly challenging. However, says Chowdhary, “there aren’t a lot of automated

solutions for these because of the nature of the crops. But this a big area of

research and one of the grand challenges in the field.”

Specialty crops are usually grown on a smaller scale than row crops, mak-

ing it more difficult to justify automation economically. And then there are the

plants themselves. “In the robotics world, we

hear a lot about the robot-human interface,”

says WSU’s Zhang. “However, in specialty

crop agriculture there is also the critical issue

of the robot-plant interface, because each

plant grows naturally and differently in its own,

nonstandard way.”

Many specialty crops are more fragile than row crops—think of berries

versus corn. And row crops are usually annual plants that can be destroyed

during harvest, while many specialty crops are perennials, such as apple

trees and grape vines. That means that robots need to perform tasks without

damaging the plants.

While specialty crop automation is far from the norm, there are automat-

While specialty crop automation is far from the norm, there are automated solu-tions on the market or in development, especially for tasks such as weeding and spraying.


ed solutions on the market or in development, especially for tasks such as

weeding and spraying. San Diego-based Vision Robotics offers a robotic

lettuce thinner that has been helping farmers address labor shortages for

Local, Fresh... and Robotic

In January 2020, the Fifth Season company opened up a robot-

ics-driven indoor vertical farm in Braddock, Pa., a town just outside

Pittsburgh, and began growing spinach, salad blends, and other fresh

greens for sale in local stores.

The facility is a closed and controlled environment, with an extensive

system of robotic conveyers and vertical lifts moving plants through

the hydroponic growing process. The system seeds plants in small

containers and places them in modular, movable trays. These are auto-

matically moved to a growing room and placed on shelves reaching 30

feet high, with each shelf providing a specific environment of lighting

and nutrients. As plants grow and need new conditions, the system

automatically shifts flats around to the appropriate shelves.

Some activities, such as inspection of plants and parts of the

packaging process, still involve humans. But in that case, “instead of

moving people to the plants, we move the plants to the people,” says

Brac Webb, co-founder and CTO/COO of Fifth Season.

The movement of the flats is directed by a proprietary artificial intel-

ligence software system, based on recipes that specify what each flat

of plants needs when. “We track every one of the nearly 8,000 growing

trays as they move through the farm,” says Webb. “We grow a bunch

of different things in a bunch of different ways—it’s really too complex

for humans to keep track of.”

“With this controlled environment agriculture, we can really optimize

what the plant gets for every stage of its lifecycle,” Webb continues.

The result is consistent production of healthy plants with the right qual-

ities. And, says Webb, “we can shave up to two weeks off of the time

it would normally take to grow a plant, because there are no ‘gaps’ in

the ideal conditions.” At the same time, the company’s approach helps

keep labor and energy costs down.

The system naturally generates a great deal of data about plants and

detailed growing conditions. With that data, and the ability to trace the

history of every flat of plants, the company plans to use analytics and

deep learning technology to uncover trends and drive ongoing im-

provements in recipes and processes.


several years. Typically, farmers “overplant” lettuce seeds to make sure that

enough plants take hold and grow. Once the plants emerge, the farmer goes

back and thins out the extras—traditionally by hand with a hoe—leaving the

healthy plants growing about 10 inches apart along the row.

Towed behind a tractor, the Vision Robotics lettuce thinner handles this

task by spraying the unwanted plants with fertilizer, which kills lettuce in its

early stages of growth. This simultaneously adds fertilizer to the field for the

benefit of the remaining lettuce.

The lettuce thinner relies on the company’s core machine-vision technol-

ogy. Each spraying line on the robot has a camera, and the system uses a

proprietary algorithm to identify the “good” lettuce and guide the sprayer. The

thinner can be towed at up to 3 mph, says Tony Koselka, chief operating offi-

cer at Vision Robotics. However, he says, “the vision system could probably

operate closer to 10 miles an hour. The limit is the ability to turn the sprayer

on and off fast enough to precisely target the spray.”

Vision Robotics is using a similar approach in its development of a me-

chanical weeder, which drags pairs of blades

through the ground to kill weeds. Guided by

the vision system, the blades open and close

to miss the desirable plants. The company has

also been using deep learning with these im-

plements, allowing them to get more accurate

over time.

“We have another weeder that looks for a certain weed that was more yel-

low than the green crop,” says Koselka. “Then one year, the weeds didn’t turn

yellow as early as they had in past seasons. We simply created a new deep

learning training set which effectively handled the new conditions.”

Spraying, weeding, and even pruning for specialty crops are moving ahead

rapidly. But the actual harvesting of those crops still presents a significant

challenge. While some crops—such as nuts or tomatoes that are going to be

crushed for processing—can be harvested mechanically, things like fresh fruit

and berries present developers with some complex problems.

For example, tomatoes on a given plant do not all ripen at the same time.

The robot needs to identify the ripe fruit and leave the unripe fruit unharmed.

And it needs to plan a path for its arm to reach the ripe tomato, navigating

past stems, foliage, and other tomatoes, without doing any damage.

“The actuators—meaning the picking hands—are the thing that’s furthest

behind right now,” says Vision Robotic’s Koselka. These need to have the

force to pull the crop in question from the plant and the dexterity to avoid

harming the crop or the plant. Various approaches are being tried out, such

as suction cup-type devices for apples or blasts of air to remove berries.

Spraying, weeding, and even pruning for specialty crops are moving ahead rapidly. But the actual harvesting of those crops still presents a significant challenge.


Girish Chowdhary and his UIUC collaborator Girish Krishnan also are

exploring the use of soft robotics in agriculture, as well as the creation of

robots with octopus-like appendages.

“Soft robots could really be one of the key parts of the solution to the

plant manipulation problem,” Chowdhary says. “Imagine, for example, three

tubes together and each of them has a different winding, so when you pres-

surize the tubes, they all bend in a specific way. By controlling the pressure

on the tube, you could get that soft robot to move in very dexterous ways

and wrap gently around a plant and grasp a berry.” Chowdhary’s team is

working with the USDA and National Science Foundation funding for this

project, which he says is in the early research stage, with any commercial-

ization still several years in the future.


Getting Smarter

In many areas of agriculture, automation and robotics are still evolving and

emerging, and new possibilities will continue to open up. Robots will keep

getting smarter, and automated equipment can play a key role in the growing

use of data on the farm—collecting data from the field and using it to drive

actions and automated decision making. Emerging 5G technology will only

accelerate those data flows, and a growing range of sensors and the Internet

of Things will keep bringing improved monitoring and control capabilities.

“This is all enabling the concept of caring for individual plants across

the large farm as if it were a backyard garden,” says UC-Davis’s Slaughter.

“We want to be able to farm a large area at commercial scale with the same

knowledge and intimate level of care that we can provide in a backyard

garden.”

As with any relatively new technology-based revolution, there are still

a range of problems to be solved, from bringing costs down to training

the farm workforce for more technology-oriented jobs—all of which spells

opportunity. “Robotics is typically three things—the mechanisms, the sen-

sors and the computer hardware, and the algorithms and software,” says

Chowdhary. “We need to keep developing and advancing in all three of these

areas to make better, and more useful, robots for agriculture.”

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