Nvidia goes all-in on self-driving cars, including a robotic car racing league

Jen-Hsun Huang raving about the Nvidia powered Robocar for Roboracing

Nvidia doesn’t always announce new consumer graphics cards at its annual technology conference, but it was widely expected to this year. Instead, GTC 2016 is all about AI, VR, and especially self-driving cars. Following up on its announcement of the Drive PX 2 car computer, Nvidia updated its plans to ship a complete set of developer tools — fueled by its own autonomous vehicle research — for car makers, and to sponsor and help equip a robot car racing league.

DriveWorks is the power behind the Drive PX 2

A supercomputer in your trunk, like Nvidia’s Drive PX 2, isn’t much good without the software to run it. That’s where Nvidia’s DriveWorks platform comes in. First announced at CES, it is getting closer to reality with a “Spring 2016” ship date. Nvidia CEO Jen-Hsun Huang also used his keynote to go into more detail about what it will include. The developer platform starts with sensor fusion and computer vision software that can work with up to 12 cameras and other sensors to provide a comprehensive model of the vehicle’s environment. From there, advanced machine learning capability will assist with navigation, vehicle control, and path planning.

Path planning is the tricky process of deciding where to navigate the car in traffic or through an intersectionHigh-quality maps, like those from HERE, are also going to be supported. One interesting feature is support for map creation using the DriveWorks in-car platform coupled with cloud-based processing for the actual map creation. It was a little unclear from Huang’s description exactly how all this would work — except that he hopes and expects that that cloud will be populated with Nvidia’s new $130K DGX-1 supercomputer — but what is clear is that he sees this technology greatly reducing the cost of mapping areas, and of training autonomous vehicles. In particular, it should make it possible to do a better job of keeping maps up to date. Instead of needing routes to be re-driven with expensive, specialized, vehicles to pick up changes in the road layout or obstacles, data from “regular” Drive PX 2-equipped cars could be used.

Self-driving with DAVENET, or “I can do that, Dave”

Rounding out Nvidia’s DriveWorks offering will be a deep neural network (DNN) that has been trained to know how to drive. Traditionally, autonomous vehicles, such as the ones used in the DARPA challenge, have relied on manually-coded algorithms to follow a desired route, and provide vehicle control. Nvidia (along with many other current vehicle research teams) has been experimenting with using deep learning neural networks instead. According to Huang (and illustrated with a demo video), after only 3,000 miles of supervised driving, its car — powered by its DAVENET (formerly named DRIVENET) neural network — was able to navigate on freeways, country roads, gravel driveways, and in the rain.

The computing power required to recoginize and accurately track dozens of objects across many cameras and sensors is definitely supercomputer worthyOf course, what he showed was only a demo video. But all in all, it was quite a remarkable achievement when contrasted with the hundreds of man years of coding that went into the much-less-sophisticated driving of the DARPA challenge cars only 10 years ago. Obviously, Nvidia isn’t suddenly planning to become a car company, but it will be providing its technology as part of the set of tools for the auto industry to use to take advantage of its Drive PX 2. Huang showed, for example, how the PX 2’s ability to process 12 cameras at once not only assists driving safely through traffic and obstacles, but builds a sufficient model of the world around it to allow for adjusting to road conditions and routing.

Roborace: Full-size robotic car racing

For decades, car and auto accessory manufacturers have used racing as both an advertising tool and a way to advance their own research and development. Whether it is F1, IndyCar, or NASCAR, factory teams are ever present and always using what they learn to help them with their next generation of street vehicles. Now that autonomous operation is an increasingly realistic future path for road cars, bringing computing front and center in auto development, it makes sense racing should become a platform for AI-based vehicle R&D.

Nvidia's Drive PX 2 replaced a supercomputer in Baidu's autonomous vehicle project

That’s exactly what Nvidia and others are planning for the newly announced Roborace league. Piggybacking off the fast-growing Formula E (all Electric) schedule and car design, the league will feature 20 identical Roborace cars allocated to 10 teams. They will race on the same courses as Formula E, except without drivers. The cars won’t be remote-controlled, either. They’ll be fully autonomous, using an Nvidia Drive PX 2 portable supercomputer to run their software. So the teams’ innovation and differentiation will be in the software they develop for the race. The Roborace is scheduled to start alongside the 2016-2017 Formula E season, later this year. Roborace founder Dennis Sverdlov told GTC attendees he expected it to make heroes out of software developers: “It’s not possible to get competitive advantage based on how much money you put in hardware. Our heroes are not the drivers. Our heroes are engineers.”

Jealous? You too can build a (small) self-driving car!

You can DIY your own robo racecar by following along with JetsonhacksAlong with each new autonomous vehicle announcement, there is always a statement of the massive investment needed to make it happen. But for those of us who want to do more than be passive spectators, there is an exciting new opportunity to learn how to build your own — scaled-down — robotic race car. Startup JetsonHacks has taken MIT’s RACECAR autonomous car learning platform and made it accessible to the DIY community with detailed assembly instructions, and cost-saving hardware options to make it more affordable than the University’s original version. The RACECAR is a massive kit bash of an offf-the-shelf RC vehicle — a Traxxas Rally — so that all the DIY fun is concentrated on the control and programming. The brain is (naturally) a Jetson TK1, running Robot OS (ROS).

In an exclusive interview, JetsonHacks Founder Bill Jenson excitedly explained that this year will feature an upgraded model based on this Spring’s MIT Controls Course — which will be available online — and a new design featuring a more-powerful Jetson TX1. If you’d rather flex your maker muscle with a drone, he also offers a lot of great DIY drone advice based on the DJI Matrice 100 development platform.

Leave a Reply

Your email address will not be published. Required fields are marked *