According to Clearpath co-founder and CEO, Matt Rendall, OTTO taps into the same sensor-driven, high-computing backbone of Google’s self-driving car to safely and efficiently transport supplies along the same plant and warehouse paths populated by workers and equipment.

“The key difference between OTTO and previous generations of this technology is that fundamentally OTTO is off the track,” explains Rendall.

He likens the distinction to the difference between subway systems and taxis in a busy city.

“There is a time and a place for a subway system,” he says. “But when speed and efficiency are needed, there is also a time and a place for taxi cabs.”

However, creating a robot smart enough to safely traverse a busy plant is a far cry from trusting an experienced driver to get you to the office on time. To make that jump, Clearpath had to tap into the full arsenal of today’s technological tools.

A High-Tech Backbone

The biggest story in the AGV market in recent years was Amazon’s 2012 purchase of Kiva Systems.

The $775 million deal gave Amazon exclusive access to Kiva System’s line of warehousing robotics—at the time considered to be one of the most advanced in the market—and eventually deploying 15,000 of them to streamline, upset, and in all ways redefine its complex order picking and delivery process.

According to Rendall, Kiva’s unique, extremely efficiency system was years ahead of its time when it was conceived and built 13 years ago.

However, he notes, the technological tools at the disposal of contemporary robot makers have changed dramatically since then.

“Vehicles like these require 2D barcodes on the floor at approximately three-foot intervals,” he explains. “So if you wanted to enable 100,000 sq ft of fulfillment, you would also need to deploy 100,000 sq ft of barcodes.”

On top of that, he adds, those systems aren’t safe for collaboration with humans. Together, this means the systems require a lot of unpopulated space and a lot of infrastructure to even get started.

The sweet spot of that generation of device, Rendall says, is in greenfield spaces—brand new warehouses and facilities that can be custom-built with the space and infrastructure they require.

However, that is not a luxury most would-be users can afford.

More to the point, it is no longer necessary.

“The technology landscape has fundamentally changed in the last 13 years,” Rendall argues. “Smarphones, the Internet, cloud computing, the Industrial Internet of Things—these are all of the enabling pillars that come together in this beautiful way to make self-driving vehicles possible for manufacturing and for warehousing.”

Computational power alone, he says, has increased exponentially in this time.

“It all starts with computation. We’re able to build a vehicle that has much more powerful machine computation ability than you could have done 10 years ago, 13 years ago, for the same price,” he explains. “That means you’re able to do much more intensive algorithms onboard the robot.”

And that’s the key to the self-driving puzzle: the robot is smart enough to make critical decisions itself. Thanks to the high-tech backing it inherited from Google and the consumer technology industry, OTTO carries with it all of the sensors, computers, and internal logic capabilities to effectively plot courses, avoid obstacles, and safely interact with human coworkers in a way no other AGV has ever mastered.

By going off the track and off the barcode grid, it is able to access whole new aspects of the manufacturing process.

“When you remove those barcodes, you enable the ability to operate in close proximity to humans,” Rendall explains. “This means you can not only do brownfield fulfillment, you can also do brownfield manufacturing.

“You can get deeper into the warehouse, or deeper into the factory than ever before.”

The next part of the challenge comes down to training and experience

In this case, designing for industrial automation gave Clearpath a big advantage.

“On public roads, you need to build your system to be robust enough to protect against a child jumping out from between two cars chasing a ball in foggy conditions,” Rendall says. “In a factory, though, people are trained how to be safe. They already know how to interact with fork trucks and production equipment.”

OTTO, he says, fits directly into that knowledge base.

“There’s a level of care that you can expect from people that interact with heavy machinery,” he says. “We start with that and then train the material flow engineers, the shift supervisors, and the floor staff so they can understand what safe operating procedures are around the robots.”

The Power of Innovation

Looking at OTTO objectively, it’s safe to call this an extremely exciting innovation. After all, if self-driving factory robots aren’t a harbinger of an amazing sci-fi future, nothing is.

But what is more exciting is the speed at which Clearpath brought this technology to market.

Clearpath Robotics began in the dorms at Ontario’s University of Waterloo by a group of robot hobbyists and mechatronics engineering majors, just in 2008.

Since then, the company has experimented with a few self-driving military drones and vehicles—include a minefield-clearing concept that provided the company with its name.

The company didn’t sell its 1,000th robot until 2014, and until 2015 it hadn’t targeted any robots at all for the manufacturing and material handling space.

And yet in 2016, Clearpath is already on the market with a fully robust, smart machine that is getting ready to some very heavy lifting at a few of the country’s top manufacturers.

That seems like an incredible feat. And it is. But it is exactly the kind of innovation we should expect in today’s tech-rich, tech-obsessed environment.

“We knew going into this that we weren’t experts in supply chain or manufacturing optimization from a material flow planning perspective, and we had no misillusions about that,” Rendall explains.

But, he says, they did understand robotics and they had plenty of experience playing in the tech space that surrounds it. And that, he says, is enough to build just about anything.

“The way that I think about it is, the fundamental pillars that have enabled self-driving vehicles for factories are computing, which led into mobile computing and smartphones, and then Internet which hooks that into big data and predictive analytics,” he says. “All you need then is an investment in robotics and unmanned vehicles.”

In essence, he is describing an environment that it ripe with the raw ingredients for innovation. The consumer world is pumping out smart devices, powerful and cheap sensors, and incredible IoT innovations that, to date, still have no direct market in the consumer world.

However, facing unprecedented need for higher productivity, improved logistics efficiency, and manufacturing proficiency, the industrial world presents a desperate and legitimate need for smart technologies.

There is that old mandate in the manufacturing world: do more, better, with less. That has been the reigning principle in the industry for generations, and it’s not showing any sign of easing. It is, in fact, only getting more extreme.

Tapping into the right combination of the full and already robust technological landscape surrounding manufacturing—all of the modern Internet capabilities, cloud computing, robotics, smartphones, and sensors—can arm manufacturers with exactly what they need to win this fight.

And it looks like they are starting to win.

“Unless you spend a lot of time in [Google’s self-driving test grounds] Mountainview, Calif., you’ve probably never seen a self-driving vehicle on the road,” Rendall says. “What I’m most excited about is that people will see self-driving vehicles in factories much sooner than they will ever see them on the road.”