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CES 2018: Waiting for the $100 Lidar

#artificialintelligence

For the past decade, the easiest way to spot a self-driving car was to look for the distinctive spinning bucket mounted to its roof. The classic lidar design pioneered by Velodyne spins 64 lasers through 360 degrees, producing a three-dimensional view of the car's surroundings from the reflected laser beams. That complicated and bulky set-up has traditionally also been expensive. Velodyne's US $75,000 lidar famously cost several times the sticker price of the Toyota Priuses that formed the nucleus of Google's original self-driving car fleet. Those days are long gone.


NVIDIA unveils its powerful Xavier SOC for self-driving cars

Engadget

As the need for more powerful processors in the emerging self-driving and semi-autonomous car grows, NVIDIA is making sure it stays ahead of the trend. At CES, the GPU-building powerhouse unveiled the Xavier SOC for AI car systems the company announced at last year's CES. The Xavier has over 9 billion transistors with a custom 8-core CPU, a 512-core Volta GPU, an 8K HDR video processor, a deep-learning accelerator and new computer-vision accelerators. NVIDIA says the SOC can perform 30 trillion operations per second using only 30 watts of power. NVIDIA says that's 15 times more efficient than the previous architecture.


Video Friday: Drone Fireworks, Cozmo Rap, and Justin Timberlake

IEEE Spectrum Robotics Channel

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. You won't want to miss the 2028 Pan-Asian Deep Learning Conference in Kuala Lumpur: Call me a hater if you want, but at least for now, pretty sure that's fake. What's funny, though, is that those first five demos are straight out of the standardized humanoid robot demo handbook (which doesn't exist).


Toyota's new self-driving test car can better recognize small objects

Engadget

Toyota Research Institute (TRI) will debut the latest version of its automated driving research vehicle at CES next week. TRI had three major goals with this latest model and Platform 3.0 incorporates them all into a car with more perception capabilities, a design that's easier to produce at scale and a much sleeker look. "To elevate our test platform to a new level, we tapped Toyota's design and engineering expertise to create an all-new test platform that has the potential to be a benchmark in function and style," TRI CEO Gill Pratt said in a statement. First, the vehicle now has 360-degree LiDAR sensing -- previous platforms only had forward-facing LiDAR sensing capabilities -- and new shorter-range LiDAR sensors placed lower to the ground allow for detection of smaller objects like road debris or children. Secondly, Platform 3.0, built on a Lexus LS 600hL, will go into low-volume production this spring and will come in two versions.


337

AI Magazine

The t.estbed simulates a class of a distributed knowledge-based THERE ARE TWO MAJOR T IEMES of this article. First, WC introduce readers to the emerging subdiscipline of AI called Dzstrrbuted Problem Solving, and more specifically the authors' research on Functionally Accurate, Cooperative systems Second, we discuss the st,ructure of tools that allow more thorough experimentation than has typically been performed in AI research An examplr of such a tool, the Distributed Vehicle Monitoring Testbed, will bc presented. The testbed simulates a class of dist,ributed knowledge-based problem solving systems operating on an abstracted version of a vehicle monitoring task. This presentation emphasizes how the t,estbed is structured to facilit,ate the study of a wide range of issues faced in t,he design of distributed problem solving networks. Distribut,ed Problem Solving (also called Distributed Al) combines the research interests of the fields of AI and Distributed Processing (Chandrasekaran 1981; Davis 1980, 1982; Fehling & Erman 1983).


Autonomous Driving in Traffic: Boss and the Urban Challenge

AI Magazine

In this article we introduce Boss, the autonomous vehicle that won the challenge. Boss is a complex artificially intelligent software system embodied in a 2007 Chevy Tahoe. To navigate safely, the vehicle builds a model of the world around it in real time. This model is used to generate safe routes and motion plans both on roads and in unstructured zones. An essential part of Boss's success stems from its ability to safely handle both abnormal situations and system glitches.


self-driving-cars-challenges

WIRED

In the spring of that year, the good Swedes at Volvo introduced Drive Me, a program to get regular Josefs, Frejas, Joeys, and Fayes into autonomous vehicles. By 2017, Volvo executives promised, the company would distribute 100 self-driving SUVs to families in Gothenburg, Sweden. The cars would be able to ferry their passengers through at least 30 miles of local roads, in everyday driving conditions--all on their own. "The technology, which will be called Autopilot, enables the driver to hand over the driving to the vehicle, which takes care of all driving functions," said Erik Coelingh, a technical lead at Volvo. Now, in the waning weeks of 2017, Volvo has pushed back its plans.


Before Self-Driving Cars Become Real, They Face These Challenges

WIRED

In the spring of that year, the good Swedes at Volvo introduced Drive Me, a program to get regular Josefs, Frejas, Joeys, and Fayes into autonomous vehicles. By 2017, Volvo executives promised, the company would distribute 100 self-driving SUVs to families in Gothenburg, Sweden. The cars would be able to ferry their passengers through at least 30 miles of local roads, in everyday driving conditions--all on their own. "The technology, which will be called Autopilot, enables the driver to hand over the driving to the vehicle, which takes care of all driving functions," said Erik Coelingh, a technical lead at Volvo. Now, in the waning weeks of 2017, Volvo has pushed back its plans.


A new Apple patent hints that its self-driving cars might minimize map usage

#artificialintelligence

This story was delivered to BI Intelligence Transportation and Logistics Briefing subscribers. To learn more and subscribe, please click here. Apple has filed a patent for an autonomous navigation system for vehicles that could minimize the role that maps would play in a self-driving car, reports CNBC. The patent details how Apple's system would leverage its AI capabilities and vehicle sensors to let a car navigate a road without referring to any external data sources, potentially heralding a marked departure from many other companies competing to develop self-driving vehicle systems. Apple is looking to leverage its advanced artificial intelligence (AI) systems as well as its visual processing expertise -- developed initially to improve the iPhone -- to offer a different approach to the autonomous car than many other aspirants.


Redefining 'Safety' For Self-Driving Cars

International Business Times

The event, in which no one was injured and no property was seriously damaged, attracted media and public attention in part because one of the vehicles was driving itself – and because that shuttle had been operating for only less than an hour before the crash. It's not the first collision involving a self-driving vehicle. Other crashes have involved Ubers in Arizona, a Tesla in "autopilot" mode in Florida and several others in California. But in nearly every case, it was human error, not the self-driving car, that caused the problem. In Las Vegas, the self-driving shuttle noticed a truck up ahead was backing up, and stopped and waited for it to get out of the shuttle's way.