“Gentlemen, start your engines!” This motorsport call-to-arms has rung out at races from Le Mans to Indy for decades, but with future vehicles having neither an engine nor a human behind the wheel, the well-worn phrase is headed for the archives.
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At the end of 2015, Denis Sverdlov, CEO of auto manufacturer Kinetik, announced a joint venture between Formula E and Kinetik to create the Roborace self-driving race series within a year. Roborace will feature 20 identical cars allocated to 10 teams. They will run on the same circuits as Formula E, except without drivers.
The cars won’t be remote-controlled, either, they’ll be fully autonomous, using the NVIDIA Drive PX 2 supercomputer to run the software. All cars will be mechanically identical so that the winning team’s success will depend on the best artificial intelligence (AI).
In creating the new series, Sverdlov hopes to showcase self-driving cars guided by AI and powered by electricity. While this is a race series that will probably only have 20 entrants, Kinetik believes the day is not far off when self-driving cars will be the norm thereby improving the environment and road safety.
- 10x the data for the world's largest retailers. The world's largest retailers use Bossa Nova to provide insights 3x faster with double the accuracy of their manual processes.
- Walmart’s most high-profile partnership to date is with robotics startup Bossa Nova. So far in 2019, they have deployed 350 systems for inventory management across Walmart stores, with roughly one robot for each store. Other developers targeting the space include Badger Technologies and Simbe Robotics, another startup on the rise.
Let's build the future of retail. Come help us map the retail world — every store, every product, every day. Average salaries for Bossa Nova Robotics Slam Engineer: $65,215. Bossa Nova Robotics salary trends based on salaries posted anonymously by Bossa Nova Robotics employees. Bossa Nova began working with Walmart to build their retail robots in 2014, though they did not have a finished version of the product until 2017, when Walmart began testing them in 50 stores. 6 3 Other, smaller stores also began to test out the product, and Walmart rolled out an.
Nevertheless, the biggest challenge self-driving cars will have to overcome on the road is being able to react to the randomness of traffic flow, other drivers, and the fact that no two driving situations are ever the same.
AI will outmaneuver human drivers
According to Danny Shapiro, senior director of automotive at NVIDIA, the latest autonomous technology is adept at handling this type of diverse environment. By using deep learning and sensor fusion, it’s possible to build a complete three-dimensional map of everything that’s going on around the vehicle to empower the car to make better decisions than a human driver ever could.
However, this requires massive amounts of computing to interpret all the harvested data, because normally the sensors are “dumb sensors” that merely capture information. Before being actioned the information has to be interpreted. For example, a video camera records 30 frames per second (fps), where each frame is an image, made up of several color values, and thousands of pixels.
There is a massive amount of computation required to be able to take these pixels and figure out, “is that a truck?” or “is that a stationary cyclist?” or “in which direction does the road curve?” It’s this type of computer vision coupled with deep neural-network-processing that is required by self-driving cars.
Deep learning adds context to AI
Bossa Nova Robotics Walmart
Moving toward true AI, deep learning is a set of algorithms in machine learning that attempt to model high-level data concepts by using architectures of multiple non-linear transformations. Various deep learning architectures such as deep neural networks (DNNs), convolutional neural networks (CNNs), and deep belief networks are being applied to several fields such as computer vision, automatic speech recognition, natural language processing, and music/audio signal recognition where they have proven to be astoundingly responsive and accurate.
NVIDIA’s DriveWorks is one such DNN that has been trained to understand how to drive. In the past, self-driving vehicles, such as the ones competing in the DARPA challenge, have relied on manually-coded algorithms to track a desired route and control the vehicle. Now, applying DNNs, a car can navigate freeways, country roads, gravel driveways, and drive in the rain after only 3,000 miles of supervised driving.
comma.ai, a startup created by iPhone hacker George Hotz, has built a self-driving car almost entirely with CNNs that train the car how to drive. They drive the car around, and the car learns from the humans driving it what to do when it sees things in the field of view.
To help in this training, they also give the car a LIDAR that provides an accurate 3D scan of the environment to more absolutely detect the presence of cars and other users of the road. When it is time to drive, the network does not get the LIDAR data, however it does produce outputs of where it thinks the other cars are, allowing developers to test how well it is seeing things.
Related:What is LIDAR and How Does it Help Robots See?
AI and dashcams for smart vehicles
While early self-driving car companies, including Google, use expensive LIDAR sensors to visually understand what’s going on around a vehicle, Palo Alto-based NAUTO uses the type of image sensors found in “prosumer” cameras. When used in combination with motion sensors and GPS systems, accurate situational awareness can be achieved at a significantly reduced cost.
Using AI to interpret the information streamed from relatively cheap dashcams, NAUTO’s systems can detect what’s happening on the road ahead of a driver and within the vehicle.
These new technologies not only make roadway object-recognition possible, but they also improve the human-machine interface by opening up possibilities in facial and gesture recognition.
Legislators recognize AI as licensed driver
To eliminate the uncertainty around the intent of legislators to move this technology forward, U.S. vehicle safety regulators have declared the AI piloting a self-driving Google car will be considered a legal driver under federal law.
In a recent letter sent to Google, NHTSA confirmed that it “will interpret ‘driver’ in the context of Google’s described motor vehicle design as referring to the (self-driving system), and not to any of the vehicle occupants.”
The stage is set for AI to dominate our roads, and not only in racecars on closed circuits.
About the Author
Peter Els, an automotive engineer by profession, is a freelance writer who informs and entertains industry professionals and car enthusiasts alike. Check out more of Peter’s musing on cars at his Writing About Cars blog.
A Bossa Nova robot scanning a shelf at a Walmart in Auburn, Washington | |
| Type | Private |
|---|---|
| Industry | Robotics |
| Founded | 2005; 16 years ago in Pittsburgh, Pennsylvania, United States |
| Founders | |
| Headquarters | San Francisco, California , |
Key people |
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| Website | www.bossanova.com |
Bossa Nova Robotics is a startuprobotics company that manufactures inventory control robots for use in retail stores. They are best known for supplying these robots to Walmart stores,[1][2] in their effort to better compete with Amazon.[3][4]
Their Auto-S line of robots scans store shelves by beaming light on them and snapping photos using 2D and 3D cameras, as well as utilizing lidar to navigate and detect if anything is stocked in a shelf.[5] From this it can detect out-of-stock items, incorrect prices, and other irregularities more efficiently and accurately than a human.[6][7]
History[edit]
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Bossa Nova was founded in 2005 by students attending Carnegie Mellon University, spinning out from their Robotics Institute.[2][7] They began creating robotic toys, such as a robotic penguin and a programmable gorilla, though they did not see much success on the market.[2] In 2012, Bossa Nova unveiled a ballbot named mObi, which featured a tablet screen on the top and was to act as a personal assistant.[8]
Bossa Nova began working with Walmart to build their retail robots in 2014, though they did not have a finished version of the product until 2017, when Walmart began testing them in 50 stores.[6][3] Other, smaller stores also began to test out the product, and Walmart rolled out an additional 300 robots in 2019.[2][6][9] Walmart ended its contract with Bossa Nova in late 2020.[10]
References[edit]
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- ^Schwab, Katharine (August 29, 2019). 'Walmart's robot army has arrived'. Fast Company. Retrieved September 15, 2019.
- ^ abcdHeater, Brian (April 10, 2019). 'The startup behind Walmart's shelf-scanning robots'. TechCrunch. Retrieved September 15, 2019.
- ^ abPerez, Sarah (April 9, 2019). 'Walmart to expand in-store tech, including Pickup Towers for online orders and robots'. TechCrunch. Retrieved September 15, 2019.
- ^Vanian, Jonathan (March 26, 2018). 'Why Walmart Is Testing Robots In Stores—and Here's What It Learned'. Fortune. Retrieved September 15, 2019.
- ^Simon, Matt (January 12, 2018). 'Please Do Not Assault the Towering Robot That Roams Walmart'. Wired. Retrieved September 15, 2019.
- ^ abcGreen, Dennis (April 15, 2019). 'A small robotics company created a device retailers were clamoring for, and now Walmart is putting it in 350 stores'. Business Insider. Retrieved September 15, 2019.
- ^ abKolodny, Lora (June 21, 2018). 'Bossa Nova just raised another $29 million for its grocery store robots used by Walmart'. CNBC. Retrieved September 14, 2019.
- ^Gaskin, James (November 8, 2012). 'Bossa Nova's mObi, first 'ballbot,' rolls onstage'. ITWorld. Retrieved September 15, 2019.
- ^Banker, Steve (April 19, 2019). 'Walmart Expands Use of Bossa Nova's Robots from 50 to 350 Stores'. Forbes. Retrieved September 15, 2019.
- ^Nassauer, Sarah (November 2, 2020). 'Walmart Scraps Plan to Have Robots Scan Shelves'. The Wall Street Journal. Retrieved November 3, 2020.
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