Tag Archives: sensors

#432893 These 4 Tech Trends Are Driving Us ...

From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies.

Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference.

Today, the process of feeding humanity is extremely inefficient.

If we could radically reinvent what we eat, and how we create that food, what might you imagine that “future of food” would look like?

In this post we’ll cover:

Vertical farms
CRISPR engineered foods
The alt-protein revolution
Farmer 3.0

Let’s dive in.

Vertical Farming
Where we grow our food…

The average American meal travels over 1,500 miles from farm to table. Wine from France, beef from Texas, potatoes from Idaho.

Imagine instead growing all of your food in a 50-story tall vertical farm in downtown LA or off-shore on the Great Lakes where the travel distance is no longer 1,500 miles but 50 miles.

Delocalized farming will minimize travel costs at the same time that it maximizes freshness.

Perhaps more importantly, vertical farming also allows tomorrow’s farmer the ability to control the exact conditions of her plants year round.

Rather than allowing the vagaries of the weather and soil conditions to dictate crop quality and yield, we can now perfectly control the growing cycle.

LED lighting provides the crops with the maximum amount of light, at the perfect frequency, 24 hours a day, 7 days a week.

At the same time, sensors and robots provide the root system the exact pH and micronutrients required, while fine-tuning the temperature of the farm.

Such precision farming can generate yields that are 200% to 400% above normal.

Next let’s explore how we can precision-engineer the genetic properties of the plant itself.

CRISPR and Genetically Engineered Foods
What food do we grow?

A fundamental shift is occurring in our relationship with agriculture. We are going from evolution by natural selection (Darwinism) to evolution by human direction.

CRISPR (the cutting edge gene editing tool) is providing a pathway for plant breeding that is more predictable, faster and less expensive than traditional breeding methods.

Rather than our crops being subject to nature’s random, environmental whim, CRISPR unlocks our capability to modify our crops to match the available environment.

Further, using CRISPR we will be able to optimize the nutrient density of our crops, enhancing their value and volume.

CRISPR may also hold the key to eliminating common allergens from crops. As we identify the allergen gene in peanuts, for instance, we can use CRISPR to silence that gene, making the crops we raise safer for and more accessible to a rapidly growing population.

Yet another application is our ability to make plants resistant to infection or more resistant to drought or cold.

Helping to accelerate the impact of CRISPR, the USDA recently announced that genetically engineered crops will not be regulated—providing an opening for entrepreneurs to capitalize on the opportunities for optimization CRISPR enables.

CRISPR applications in agriculture are an opportunity to help a billion people and become a billionaire in the process.

Protecting crops against volatile environments, combating crop diseases and increasing nutrient values, CRISPR is a promising tool to help feed the world’s rising population.

The Alt-Protein/Lab-Grown Meat Revolution
Something like a third of the Earth’s arable land is used for raising livestock—a massive amount of land—and global demand for meat is predicted to double in the coming decade.

Today, we must grow an entire cow—all bones, skin, and internals included—to produce a steak.

Imagine if we could instead start with a single muscle stem cell and only grow the steak, without needing the rest of the cow? Think of it as cellular agriculture.

Imagine returning millions, perhaps billions, of acres of grazing land back to the wilderness? This is the promise of lab-grown meats.

Lab-grown meat can also be engineered (using technology like CRISPR) to be packed with nutrients and be the healthiest, most delicious protein possible.

We’re watching this technology develop in real time. Several startups across the globe are already working to bring artificial meats to the food industry.

JUST, Inc. (previously Hampton Creek) run by my friend Josh Tetrick, has been on a mission to build a food system where everyone can get and afford delicious, nutritious food. They started by exploring 300,000+ species of plants all around the world to see how they can make food better and now are investing heavily in stem-cell-grown meats.

Backed by Richard Branson and Bill Gates, Memphis Meats is working on ways to produce real meat from animal cells, rather than whole animals. So far, they have produced beef, chicken, and duck using cultured cells from living animals.

As with vertical farming, transitioning production of our majority protein source to a carefully cultivated environment allows for agriculture to optimize inputs (water, soil, energy, land footprint), nutrients and, importantly, taste.

Farmer 3.0
Vertical farming and cellular agriculture are reinventing how we think about our food supply chain and what food we produce.

The next question to answer is who will be producing the food?

Let’s look back at how farming evolved through history.

Farmers 0.0 (Neolithic Revolution, around 9000 BCE): The hunter-gatherer to agriculture transition gains momentum, and humans cultivated the ability to domesticate plants for food production.

Farmers 1.0 (until around the 19th century): Farmers spent all day in the field performing backbreaking labor, and agriculture accounted for most jobs.

Farmers 2.0 (mid-20th century, Green Revolution): From the invention of the first farm tractor in 1812 through today, transformative mechanical biochemical technologies (fertilizer) boosted yields and made the job of farming easier, driving the US farm job rate down to less than two percent today.

Farmers 3.0: In the near future, farmers will leverage exponential technologies (e.g., AI, networks, sensors, robotics, drones), CRISPR and genetic engineering, and new business models to solve the world’s greatest food challenges and efficiently feed the eight-billion-plus people on Earth.

An important driver of the Farmer 3.0 evolution is the delocalization of agriculture driven by vertical and urban farms. Vertical farms and urban agriculture are empowering a new breed of agriculture entrepreneurs.

Let’s take a look at an innovative incubator in Brooklyn, New York called Square Roots.

Ten farm-in-a-shipping-containers in a Brooklyn parking lot represent the first Square Roots campus. Each 8-foot x 8.5-foot x 20-foot shipping container contains an equivalent of 2 acres of produce and can yield more than 50 pounds of produce each week.

For 13 months, one cohort of next-generation food entrepreneurs takes part in a curriculum with foundations in farming, business, community and leadership.

The urban farming incubator raised a $5.4 million seed funding round in August 2017.

Training a new breed of entrepreneurs to apply exponential technology to growing food is essential to the future of farming.

One of our massive transformative purposes at the Abundance Group is to empower entrepreneurs to generate extraordinary wealth while creating a world of abundance. Vertical farms and cellular agriculture are key elements enabling the next generation of food and agriculture entrepreneurs.

Conclusion
Technology is driving food abundance.

We’re already seeing food become demonetized, as the graph below shows.

From 1960 to 2014, the percent of income spent on food in the U.S. fell from 19 percent to under 10 percent of total disposable income—a dramatic decrease over the 40 percent of household income spent on food in 1900.

The dropping percent of per-capita disposable income spent on food. Source: USDA, Economic Research Service, Food Expenditure Series
Ultimately, technology has enabled a massive variety of food at a significantly reduced cost and with fewer resources used for production.

We’re increasingly going to optimize and fortify the food supply chain to achieve more reliable, predictable, and nutritious ways to obtain basic sustenance.

And that means a world with abundant, nutritious, and inexpensive food for every man, woman, and child.

What an extraordinary time to be alive.

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Posted in Human Robots

#432878 Chinese Port Goes Full Robot With ...

By the end of 2018, something will be very different about the harbor area in the northern Chinese city of Caofeidian. If you were to visit, the whirring cranes and tractors driving containers to and fro would be the only things in sight.

Caofeidian is set to become the world’s first fully autonomous harbor by the end of the year. The US-Chinese startup TuSimple, a specialist in developing self-driving trucks, will replace human-driven terminal tractor-trucks with 20 self-driving models. A separate company handles crane automation, and a central control system will coordinate the movements of both.

According to Robert Brown, Director of Public Affairs at TuSimple, the project could quickly transform into a much wider trend. “The potential for automating systems in harbors and ports is staggering when considering the number of deep-water and inland ports around the world. At the same time, the closed, controlled nature of a port environment makes it a perfect proving ground for autonomous truck technology,” he said.

Going Global
The autonomous cranes and trucks have a big task ahead of them. Caofeidian currently processes around 300,000 TEU containers a year. Even if you were dealing with Lego bricks, that number of units would get you a decent-sized cathedral or a 22-foot-long aircraft carrier. For any maritime fans—or people who enjoy the moving of heavy objects—TEU stands for twenty-foot equivalent unit. It is the industry standard for containers. A TEU equals an 8-foot (2.43 meter) wide, 8.5-foot (2.59 meter) high, and 20-foot (6.06 meter) long container.

While impressive, the Caofeidian number pales in comparison with the biggest global ports like Shanghai, Singapore, Busan, or Rotterdam. For example, 2017 saw more than 40 million TEU moved through Shanghai port facilities.

Self-driving container vehicles have been trialled elsewhere, including in Yangshan, close to Shanghai, and Rotterdam. Qingdao New Qianwan Container Terminal in China recently laid claim to being the first fully automated terminal in Asia.

The potential for efficiencies has many ports interested in automation. Qingdao said its systems allow the terminal to operate in complete darkness and have reduced labor costs by 70 percent while increasing efficiency by 30 percent. In some cases, the number of workers needed to unload a cargo ship has gone from 60 to 9.

TuSimple says it is in negotiations with several other ports and also sees potential in related logistics-heavy fields.

Stable Testing Ground
For autonomous vehicles, ports seem like a perfect testing ground. They are restricted, confined areas with few to no pedestrians where operating speeds are limited. The predictability makes it unlike, say, city driving.

Robert Brown describes it as an ideal setting for the first adaptation of TuSimple’s technology. The company, which, amongst others, is backed by chipmaker Nvidia, have been retrofitting existing vehicles from Shaanxi Automobile Group with sensors and technology.

At the same time, it is running open road tests in Arizona and China of its Class 8 Level 4 autonomous trucks.

The Camera Approach
Dozens of autonomous truck startups are reported to have launched in China over the past two years. In other countries the situation is much the same, as the race for the future of goods transportation heats up. Startup companies like Embark, Einride, Starsky Robotics, and Drive.ai are just a few of the names in the space. They are facing competition from the likes of Tesla, Daimler, VW, Uber’s Otto subsidiary, and in March, Waymo announced it too was getting into the truck race.

Compared to many of its competitors, TuSimple’s autonomous driving system is based on a different approach. Instead of laser-based radar (LIDAR), TuSimple primarily uses cameras to gather data about its surroundings. Currently, the company uses ten cameras, including forward-facing, backward-facing, and wide-lens. Together, they produce the 360-degree “God View” of the vehicle’s surroundings, which is interpreted by the onboard autonomous driving systems.

Each camera gathers information at 30 frames a second. Millimeter wave radar is used as a secondary sensor. In total, the vehicles generate what Robert Brown describes with a laugh as “almost too much” data about its surroundings and is accurate beyond 300 meters in locating and identifying objects. This includes objects that have given LIDAR problems, such as black vehicles.

Another advantage is price. Companies often loathe revealing exact amounts, but Tesla has gone as far as to say that the ‘expected’ price of its autonomous truck will be from $150,0000 and upwards. While unconfirmed, TuSimple’s retrofitted, camera-based solution is thought to cost around $20,000.

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Posted in Human Robots

#432572 Robots Can Swim, Fetch, Lift, and Dance. ...

Robotics has come a long way in the past few years. Robots can now fetch items from specific spots in massive warehouses, swim through the ocean to study marine life, and lift 200 times their own weight. They can even perform synchronized dance routines.

But the really big question is—can robots put together an Ikea chair?

A team of engineers from Nanyang Technological University in Singapore decided to find out, detailing their work in a paper published last week in the journal Science Robotics. The team took industrial robot arms and equipped them with parallel grippers, force-detecting sensors, and 3D cameras, and wrote software enabling the souped-up bots to tackle chair assembly. The robots’ starting point was a set of chair parts randomly scattered within reach.

As impressive as the above-mentioned robotic capabilities are, it’s worth noting that they’re mostly limited to a single skill. Putting together furniture, on the other hand, requires using and precisely coordinating multiple skills, including force control, visual localization, hand-eye coordination, and the patience to read each step of the manual without rushing through it and messing everything up.

Indeed, Ikea furniture, while meant to be simple and user-friendly, has left even the best of us scratching our heads and holding a spare oddly-shaped piece of wood as we stare at the desk or bed frame we just put together—or, for the less even-tempered among us, throwing said piece of wood across the room.

It’s a good thing robots don’t have tempers, because it took a few tries for the bots to get the chair assembly right.

Practice makes perfect, though (or in this case, rewriting code makes perfect), and these bots didn’t give up so easily. They had to hone three different skills: identifying which part was which among the scattered, differently-shaped pieces of wood, coordinating their movements to put those pieces in the right place, and knowing how much force to use in various steps of the process (i.e., more force is needed to connect two pieces than to pick up one piece).

A few tries later, the bots were able to assemble the chair from start to finish in about nine minutes.

On the whole, nicely done. But before we applaud the robots’ success too loudly, it’s important to note that they didn’t autonomously assemble the chair. Rather, each step of the process was planned and coded by engineers, down to the millimeter.

However, the team believes this closely-guided chair assembly was just a first step, and they see a not-so-distant future where combining artificial intelligence with advanced robotic capabilities could produce smart bots that would learn to assemble furniture and do other complex tasks on their own.

Future applications mentioned in the paper include electronics and aircraft manufacturing, logistics, and other high-mix, low-volume sectors.

Image Credit: Francisco Suárez-Ruiz and Quang-Cuong Pham/Nanyang Technological University Continue reading

Posted in Human Robots

#432549 Your Next Pilot Could Be Drone Software

Would you get on a plane that didn’t have a human pilot in the cockpit? Half of air travelers surveyed in 2017 said they would not, even if the ticket was cheaper. Modern pilots do such a good job that almost any air accident is big news, such as the Southwest engine disintegration on April 17.

But stories of pilot drunkenness, rants, fights and distraction, however rare, are reminders that pilots are only human. Not every plane can be flown by a disaster-averting pilot, like Southwest Capt. Tammie Jo Shults or Capt. Chesley “Sully” Sullenberger. But software could change that, equipping every plane with an extremely experienced guidance system that is always learning more.

In fact, on many flights, autopilot systems already control the plane for basically all of the flight. And software handles the most harrowing landings—when there is no visibility and the pilot can’t see anything to even know where he or she is. But human pilots are still on hand as backups.

A new generation of software pilots, developed for self-flying vehicles, or drones, will soon have logged more flying hours than all humans have—ever. By combining their enormous amounts of flight data and experience, drone-control software applications are poised to quickly become the world’s most experienced pilots.

Drones That Fly Themselves
Drones come in many forms, from tiny quad-rotor copter toys to missile-firing winged planes, or even 7-ton aircraft that can stay aloft for 34 hours at a stretch.

When drones were first introduced, they were flown remotely by human operators. However, this merely substitutes a pilot on the ground for one aloft. And it requires significant communications bandwidth between the drone and control center, to carry real-time video from the drone and to transmit the operator’s commands.

Many newer drones no longer need pilots; some drones for hobbyists and photographers can now fly themselves along human-defined routes, leaving the human free to sightsee—or control the camera to get the best view.

University researchers, businesses, and military agencies are now testing larger and more capable drones that will operate autonomously. Swarms of drones can fly without needing tens or hundreds of humans to control them. And they can perform coordinated maneuvers that human controllers could never handle.

Could humans control these 1,218 drones all together?

Whether flying in swarms or alone, the software that controls these drones is rapidly gaining flight experience.

Importance of Pilot Experience
Experience is the main qualification for pilots. Even a person who wants to fly a small plane for personal and noncommercial use needs 40 hours of flying instruction before getting a private pilot’s license. Commercial airline pilots must have at least 1,000 hours before even serving as a co-pilot.

On-the-ground training and in-flight experience prepare pilots for unusual and emergency scenarios, ideally to help save lives in situations like the “Miracle on the Hudson.” But many pilots are less experienced than “Sully” Sullenberger, who saved his planeload of people with quick and creative thinking. With software, though, every plane can have on board a pilot with as much experience—if not more. A popular software pilot system, in use in many aircraft at once, could gain more flight time each day than a single human might accumulate in a year.

As someone who studies technology policy as well as the use of artificial intelligence for drones, cars, robots, and other uses, I don’t lightly suggest handing over the controls for those additional tasks. But giving software pilots more control would maximize computers’ advantages over humans in training, testing, and reliability.

Training and Testing Software Pilots
Unlike people, computers will follow sets of instructions in software the same way every time. That lets developers create instructions, test reactions, and refine aircraft responses. Testing could make it far less likely, for example, that a computer would mistake the planet Venus for an oncoming jet and throw the plane into a steep dive to avoid it.

The most significant advantage is scale: Rather than teaching thousands of individual pilots new skills, updating thousands of aircraft would require only downloading updated software.

These systems would also need to be thoroughly tested—in both real-life situations and in simulations—to handle a wide range of aviation situations and to withstand cyberattacks. But once they’re working well, software pilots are not susceptible to distraction, disorientation, fatigue, or other human impairments that can create problems or cause errors even in common situations.

Rapid Response and Adaptation
Already, aircraft regulators are concerned that human pilots are forgetting how to fly on their own and may have trouble taking over from an autopilot in an emergency.

In the “Miracle on the Hudson” event, for example, a key factor in what happened was how long it took for the human pilots to figure out what had happened—that the plane had flown through a flock of birds, which had damaged both engines—and how to respond. Rather than the approximately one minute it took the humans, a computer could have assessed the situation in seconds, potentially saving enough time that the plane could have landed on a runway instead of a river.

Aircraft damage can pose another particularly difficult challenge for human pilots: It can change what effects the controls have on its flight. In cases where damage renders a plane uncontrollable, the result is often tragedy. A sufficiently advanced automated system could make minute changes to the aircraft’s steering and use its sensors to quickly evaluate the effects of those movements—essentially learning how to fly all over again with a damaged plane.

Boosting Public Confidence
The biggest barrier to fully automated flight is psychological, not technical. Many people may not want to trust their lives to computer systems. But they might come around when reassured that the software pilot has tens, hundreds, or thousands more hours of flight experience than any human pilot.

Other autonomous technologies, too, are progressing despite public concerns. Regulators and lawmakers are allowing self-driving cars on the roads in many states. But more than half of Americans don’t want to ride in one, largely because they don’t trust the technology. And only 17 percent of travelers around the world are willing to board a plane without a pilot. However, as more people experience self-driving cars on the road and have drones deliver them packages, it is likely that software pilots will gain in acceptance.

The airline industry will certainly be pushing people to trust the new systems: Automating pilots could save tens of billions of dollars a year. And the current pilot shortage means software pilots may be the key to having any airline service to smaller destinations.

Both Boeing and Airbus have made significant investments in automated flight technology, which would remove or reduce the need for human pilots. Boeing has actually bought a drone manufacturer and is looking to add software pilot capabilities to the next generation of its passenger aircraft. (Other tests have tried to retrofit existing aircraft with robotic pilots.)

One way to help regular passengers become comfortable with software pilots—while also helping to both train and test the systems—could be to introduce them as co-pilots working alongside human pilots. Planes would be operated by software from gate to gate, with the pilots instructed to touch the controls only if the system fails. Eventually pilots could be removed from the aircraft altogether, just like they eventually were from the driverless trains that we routinely ride in airports around the world.

This article was originally published on The Conversation. Read the original article.

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Posted in Human Robots

#432352 Watch This Lifelike Robot Fish Swim ...

Earth’s oceans are having a rough go of it these days. On top of being the repository for millions of tons of plastic waste, global warming is affecting the oceans and upsetting marine ecosystems in potentially irreversible ways.

Coral bleaching, for example, occurs when warming water temperatures or other stress factors cause coral to cast off the algae that live on them. The coral goes from lush and colorful to white and bare, and sometimes dies off altogether. This has a ripple effect on the surrounding ecosystem.

Warmer water temperatures have also prompted many species of fish to move closer to the north or south poles, disrupting fisheries and altering undersea environments.

To keep these issues in check or, better yet, try to address and improve them, it’s crucial for scientists to monitor what’s going on in the water. A paper released last week by a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) unveiled a new tool for studying marine life: a biomimetic soft robotic fish, dubbed SoFi, that can swim with, observe, and interact with real fish.

SoFi isn’t the first robotic fish to hit the water, but it is the most advanced robot of its kind. Here’s what sets it apart.

It swims in three dimensions
Up until now, most robotic fish could only swim forward at a given water depth, advancing at a steady speed. SoFi blows older models out of the water. It’s equipped with side fins called dive planes, which move to adjust its angle and allow it to turn, dive downward, or head closer to the surface. Its density and thus its buoyancy can also be adjusted by compressing or decompressing air in an inner compartment.

“To our knowledge, this is the first robotic fish that can swim untethered in three dimensions for extended periods of time,” said CSAIL PhD candidate Robert Katzschmann, lead author of the study. “We are excited about the possibility of being able to use a system like this to get closer to marine life than humans can get on their own.”

The team took SoFi to the Rainbow Reef in Fiji to test out its swimming skills, and the robo fish didn’t disappoint—it was able to swim at depths of over 50 feet for 40 continuous minutes. What keeps it swimming? A lithium polymer battery just like the one that powers our smartphones.

It’s remote-controlled… by Super Nintendo
SoFi has sensors to help it see what’s around it, but it doesn’t have a mind of its own yet. Rather, it’s controlled by a nearby scuba-diving human, who can send it commands related to speed, diving, and turning. The best part? The commands come from an actual repurposed (and waterproofed) Super Nintendo controller. What’s not to love?

Image Credit: MIT CSAIL
Previous robotic fish built by this team had to be tethered to a boat, so the fact that SoFi can swim independently is a pretty big deal. Communication between the fish and the diver was most successful when the two were less than 10 meters apart.

It looks real, sort of
SoFi’s side fins are a bit stiff, and its camera may not pass for natural—but otherwise, it looks a lot like a real fish. This is mostly thanks to the way its tail moves; a motor pumps water between two chambers in the tail, and as one chamber fills, the tail bends towards that side, then towards the other side as water is pumped into the other chamber. The result is a motion that closely mimics the way fish swim. Not only that, the hydraulic system can change the water flow to get different tail movements that let SoFi swim at varying speeds; its average speed is around half a body length (21.7 centimeters) per second.

Besides looking neat, it’s important SoFi look lifelike so it can blend in with marine life and not scare real fish away, so it can get close to them and observe them.

“A robot like this can help explore the reef more closely than current robots, both because it can get closer more safely for the reef and because it can be better accepted by the marine species.” said Cecilia Laschi, a biorobotics professor at the Sant’Anna School of Advanced Studies in Pisa, Italy.

Just keep swimming
It sounds like this fish is nothing short of a regular Nemo. But its creators aren’t quite finished yet.

They’d like SoFi to be able to swim faster, so they’ll work on improving the robo fish’s pump system and streamlining its body and tail design. They also plan to tweak SoFi’s camera to help it follow real fish.

“We view SoFi as a first step toward developing almost an underwater observatory of sorts,” said CSAIL director Daniela Rus. “It has the potential to be a new type of tool for ocean exploration and to open up new avenues for uncovering the mysteries of marine life.”

The CSAIL team plans to make a whole school of SoFis to help biologists learn more about how marine life is reacting to environmental changes.

Image Credit: MIT CSAIL Continue reading

Posted in Human Robots