It starts with a seed. That seed — maybe it’s a tomato seed — gets
planted into the ground. Then it grows. And grows. Slowly, the plant
pierces through the soil, emerging into the light. Weeks to months
later, this seed becomes a plant, waist-high, bearing dozens of ripe
tomatoes. Someone picks the fruit and packs it into a box. Someone else
ships those boxes to warehouses where a restaurant or grocery buys the
tomatoes. Later, a cook will take one, cut it up and put it in a salad.
this process is still pretty low tech. Sure, there are cars and trucks
involved, but robotics? Not as much. People are still key players at
every step. But that may change, and soon.
“There are major
technologies coming in the next 10 years to make each part of farming
more efficient, more productive and hopefully healthier and less
expensive,” says Dan Steere. He heads up a company called Abundant
Robotics in Menlo Park, Calif.
In other words, robots increasingly are going to play roles in growing and preparing our food.
time the time kids in middle school become adults, the entire food
cycle may be robotic. Even now, robots help farmers. Some plant fruits,
vegetables and grains in a more efficient way. Soon, they’ll help
harvest that food more quickly. Some food warehouses already have
self-driving trucks. Robots will even help get that food onto our
plates. In fact, a robot named Sally is already doing just that. The
goal is to make the way food is produced and prepared faster, easier and
Getting seeds in the ground
field has some areas that are naturally less fertile than others.
Farmland may not be level, either. It can have areas that rise or are
lower than their surroundings. There may even be ditches. Plowing evens
out the ground somewhat, but never completely. If a creek runs through a
field, there’s always going to be land near that creek where it’s
difficult — or impossible — to plant. Soil quality also varies
throughout a field.
All of these things can impact how much food
the land can produce and how good that food will taste. And the amount
of food produced affects how much money a farmer makes.
farmers calculate how many seeds to plant and where. But land also
changes over time, so these calculations must be done over and over
again every year.
quadcopter drone moves over a farm, taking pictures from the air. This
can map the quality of the soil, any crops and even pests.ackab1/Flickr (CC-BY-SA 2.0)
Pistorius is head of a company called DroneClouds. It’s in Cape Town,
South Africa. His is one of many companies using drones to help farmers
know where to plant. Drone is slang for unmanned aerial aircraft —
a flying robot. The craft that DroneClouds uses has five cameras.
Pistorius says each camera “is essentially [like] a camera on an
iPhone.” But not a normal iPhone. He says think of each as “a very
specialized, aerial iPhone, with a very specialized, calibrated camera.”
the drone’s cameras fly overhead, they take pictures of the land. These
show field size and the different lays of the land. They also reveal
soil variation and any irrigation problems. They even show where insects
and fungus might cause problems.
Next, DroneClouds processes
those images to create a map of the field and what’s growing in it. “We
then do analyses to interpret it for the farmer,” explains Pistorius. If
the images come from an apple orchard, for instance, they might look at
how the trees are growing. They’ll note where tall weeds might cause a
brand new tree to struggle.
farmer in Zimbabwe holds a drone used for aerial crop mapping. This is
just one of the ways in which robots are becoming involved in food
production.International Maize and Wheat Improvement Center/Flickr (CC-BY-NC-SA 2.0)
To pinpoint problems, analysts compare these pictures to others of the same crop. This is called comparative analysis.
Pistorius says it’s like running a race, then comparing your time today
to what it was earlier in the season. That lets you measure how much
you’ve improved. But runners also compare their time against other
runners. So farmers compare pictures of their field to those of other
farmers. This is known as a signature-based analysis.
ideal pictures come from labs all across the world,” Pistorius says.
“Every four years, scientists from the Agricultural Research Commission
meet with labs [in the United States], and take a
bunch of signatures.” This way farmers in both countries can help each
monitored, the little plants grow. Day after day, the sun rises and
falls. Sometimes it shines, other times there’s rain. Finally, harvest
time arrives. And with it comes new, cutting-edge work in farm robotics.
For two years, Abundant Robotics has been developing a robot that picks apples. Two years? Isn’t picking apples easy?
Not if you’re a robot.
understand why apple picking is hard for a machine, let’s break down
the process. When you see an apple hanging on a tree, your eyes send a
signal to your brain. The brain processes the data in this signal — such
as the apple’s color and where it is on the tree. Instinctively, you’ll
know when the apple’s ready to pick. Your brain then tells your arm to
reach out and your hand to pull the fruit away from its branch. You hold
the apple like you would a bird — gently enough not to bruise it, but
firmly enough that it doesn’t fall away.
For people, picking an apple is so easy, even a kid can do it. But for robots, this simple activity used to be impossible.bubutu-/iStockphoto
you pick an apple, you make all these decisions quickly. But if you
needed to pick an entire field’s worth of apples, it would take a very,
very long time. After you picked one apple, you’d have to put it in a
basket. The next apple would go in there, too, and the next, until your
basket was full. Then down the ladder you’d go, where you’d have to
empty your basket before climbing back up to start again.
this for hundreds of trees would be incredibly time consuming. That’s
why people are seeking help from robots. When Abundant Robotics is done,
farmers will be able to plant more trees. And they won’t be worried
about part of their crop rotting in the field because people weren’t
able to pick it all in time.
The first problem Abundant Robotics
had to solve was acquiring the right signals. “If you don’t have a good
pair of eyes, it’s hard to do a lot of tasks in the real world,” Steere
says. So the company had to give their robot what Steere calls “a better
pair of eyes.” This system — and how it connects to a robot’s brain —
is known as computer vision. Computer vision helps the robot
see “every surface of an apple,” says Steere, in addition to judging its
size, color and weight. It can even scout for any defects in the fruit.
Such systems are rapidly improving what robots can do.
with super eyes, the apple robot still had to learn how to physically
pick the fruit without hurting it. In robotics, movement is called animation.
Steere says, “Heavy animation damages the fruit.” If it bruises the
apple or cuts through the skin, the fruit may look bad and likely won’t
sell. Rough handling also can damage trees.
So the robot must
coordinate its vision and motor skills. Think back to the apple-picking
process: You have to know which apple to pick. You have to pick it
quickly and gently. But what else? You can’t disturb apples on the tree
that still need time to grow. “The vision has to … recognize fruit,”
Steere says, and “recognize whether it’s ripe or not.” And it has to do
all that in a fraction of a second.
“People have wanted to
automate this type of agriculture for decades. It’s just never been
possible,” he says. Even after two years, his team’s work still is not
done! Abundant’s robot won’t go on sale until later this year.
Developing great tech is like farming — it takes patience.
Sorting the harvest
Coffee berries come in many colors. A new robot can quickly sort the good ones from the bad.Bonga1965/iStockphoto
the crop been picked, good fruit must be sorted from the bad. That’s
what a company called bext360 does. Instead of apples, its robot works
with cocoa, nuts, cardamom (a spice) and coffee cherries (the fruit that
holds coffee beans). Daniel Jones heads the company, based in Denver,
Take those coffee cherries. “The farmers would harvest their
coffee and place it in our machine,” Jones explains. “Then the machine
drops [the fruit] through a visioning system.” Picture a waterfall of
cherries falling. That’s what the machine stares at, all the while
taking pictures of the passing fruit. The robot then uses those pictures
to sort good coffee cherries from bad.
Machine vision and
computer vision are essentially the same thing. Abundant and best360’s
robots do different tasks. Still, the same core technology helps both of
them do it.
Before building a robot, engineers draw a design of what it will look like. This is the design for bext360’s coffee robot.Garrett Ziegler
robots also need more than computer vision to succeed. Vision can tell
bext360’s robot how to sort, but then the robot actually has to do it.
Farmers harvest coffee cherries — up to 30 kilograms (66 pounds) — from
one section of their field at a time. Then they load cherries holding
some 18,000 beans into a chute on top of the robot.
Within about 3
minutes, the robot will have individually sorted every cherry. To do
that, the robot has to take a picture of each one. Then it analyzes them
all in a mere 22 milliseconds or so. “We’ll know everything about them
in that split second that they fall through [the chute],” says Jones.
Puffs of air then push the cherries into different bins — one for good
fruit, another for rejects.
After the coffee cherry falls, the
robot shares its analysis with the farmer. “The main things [the robot
measures] are size and color and density,” says Jones. It also checks
the inside and outside of the cherry for signs of rot or disease. This
is why farmers only put cherries from one part of their field in at a
time. This information helps them know if something they tried in one
part of a field worked better than something they tried elsewhere.
The robot from bext360 is still new: Sales only started about six months ago.
Onto the plate
analyzed and sorted, a harvest now goes to a warehouse. One day, it
might get there in a self-driving semi-truck. And a self-driving
forklift might move the pallets off the truck and onto another that is
destined for a restaurant or store. Amazon already has a grocery store
just for employees that doesn’t have any human stockers or check-out
clerks: They’re all robots.
This forklift doesn’t need a driver. It can drive itself.StraSSenBahn/Wikimedia Commons (CC-BY-SA 3.0)
the food might end up with our last robot: Sally. Sally makes salads.
From the outside, she looks like a box. There’s a touchscreen and a hole
where a bowl can be placed. Inside, though, this robot’s more
complicated. “Sally is a box with the robotic components on the inside,”
notes Deepak Sekar. He heads up Chowbotics, in Redwood City, Calif.
It’s the company that makes Sally.
“There are cylinders inside the
robot that are filled with prepped ingredients,” Sekar explains. People
activate Sally by pressing the touchscreen. Diners can customize their
salads by calorie count and ingredients.
At $30,000 per robot,
Sally isn’t designed to be used at home. Chowbotics sells the robot to
schools and offices, which use Sally in cafeterias and breakrooms.
Observes Sekar: “We hear all the time that students in schools don’t
like eating from salad bars.” Why? Sekar claims they’re gross. “Because
all the ingredients are inside Sally, you don’t have to wonder if
someone sneezed on the tomatoes an hour ago — ew!,” he says. “Your salad
is always fresh and healthy.”
Robots aren’t in every part of
the field-to-plate process yet. But soon they will be. This will make
the food process cooler for us. Even more importantly, robots could one
day even out the world’s food supply. Think about it: Today, DroneClouds
helps farmers know how to plant more. bext360 helps them know how to
plant more efficiently. Abundant Robotics helps growers harvest more
quickly — which means farmers can plant more. Then Chowbotics stores
that produce in a healthier way.
Says Steere, “If there was ever a
time [for] a young person going into farming — this has gotta be one of
the most amazing times in history. The kind of things that automation
can do is going to continue to change and to evolve quickly.”