Robotics & Automation


MIT's AI makes autonomous cars drive more like humans

#artificialintelligence

Creating driverless cars capable of humanlike reasoning is a long-standing pursuit of companies like Waymo, GM's Cruise, Uber, and others. Intel's Mobileye proposes a mathematical model -- the Responsibility-Sensitive Safety (RSS) -- it describes as a "common sense" approach to on-the-road decision-making that codifies good habits like giving other cars the right of way. For its part, Nvidia is actively developing Safety Force Field, a decision-making policy in a motion-planning stack that monitors unsafe actions by analyzing real-time sensor data. Now, a team of MIT scientists are investigating an approach that leverages GPS-like maps and visual data to enable autonomous cars to learn human steering patterns, and to apply the learned knowledge to complex planned routes in previously unseen environments. Their work -- which will be presented at the International Conference on Robotics and Automation in Long Beach, California next month -- builds on end-to-end navigation systems architected by Daniel Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL).


Finding Lane Lines -- Simple Pipeline For Lane Detection.

#artificialintelligence

Identifying lanes of the road is very common task that human driver performs. This is important to keep the vehicle in the constraints of the lane. This is also very critical task for an autonomous vehicle to perform. And very simple Lane Detection pipeline is possible with simple Computer Vision techniques. This article will describe simple pipeline that can be used for simple lane detection using Python and OpenCV.


Bringing human-like reasoning to driverless car navigation

Robohub

With aims of bringing more human-like reasoning to autonomous vehicles, MIT researchers have created a system that uses only simple maps and visual data to enable driverless cars to navigate routes in new, complex environments. Human drivers are exceptionally good at navigating roads they haven't driven on before, using observation and simple tools. We simply match what we see around us to what we see on our GPS devices to determine where we are and where we need to go. In every new area, the cars must first map and analyze all the new roads, which is very time consuming. The systems also rely on complex maps -- usually generated by 3-D scans -- which are computationally intensive to generate and process on the fly.


Four Ways To Connect The Customer Journey With AI

#artificialintelligence

There's little doubt that the buzzword of 2018 was artificial intelligence. It was hard to find a headline last year in the tech space that didn't focus on how AI was going to change the world. Scrambling to be part of the revolution, companies claimed every new product was "AI-powered" or had "AI capabilities" to challenge the status quo for operations and innovations. Developers jumped in on machine learning, neural networks, natural language processing and a range of other subfields to innovate and monetize. Now that the hype has calmed a bit and brands are finally starting to implement AI-driven solutions, we are seeing a shift in the way consumers interact with brands -- from hyperpersonalized messages, to self-driving cars, to anticipating the next step in your pizza order.


Paul Pepper: Scott Christianson, Artificial Intelligence Specialist, "Face Recognition"

#artificialintelligence

University of Missouri assistant professor SCOTT CHRISTIANSON puts an app designed to assist those with visual impairments to the test using yours truly, our floor director and some wrinkled up dollar bills. Self-driving cars is becoming a reality, and while it may sound like a cool idea, PROF. SCOTT CHRISTIANSON points out a not-so-obvious morality dilemma when it comes to programming machines that are designed to make decisions that a human normally would, saying "hopefully the car will be able to avoid the accident, but there may be situations where it may not be able to, so how do we want those cars programmed?" Never mind tomorrow, machine-learning artificial intelligence is happening now! University of Missouri professor SCOTT CHRISTIANSON tells us just how much it's "creeping into our lives."


Ford's self-driving cars may have delivery robots because humans are too lazy

FOX News

Fox News Flash top headlines for May 22 are here. Check out what's clicking on Foxnews.com Ford is developing self-driving delivery vehicles it plans to launch in 2021, but there's a problem. If there isn't a driver, who's going to bring the package or pizza to your door? In tests with faux-autonomous Domino's Pizza cars, Ford discovered that a lot of people were simply too lazy to make the trip to the curb to get their orders from the car themselves, so it came up with the obvious solution: robots.


Drones may soon come with 'spidey-senses' as tiny detectors pick up on vibrations

Daily Mail - Science & tech

Drones and self-driving cars may soon come with'spidey' senses. That's according to engineers in America, who believe the unmanned machines would benefit from sensory detectors similar to those often seen in arachinds. Specifically, they're referring the hairs on a spider's legs, which are linked to special neurons called mechanoreceptors, which flag-up danger through vibrations. If machines had similar characteristics, they'd be able to navigate more effectively in dangerous environments. Until now, sensor technology hasn't always been able to process data fast enough, or as smoothly, as nature.


U.S. Postal Service Is Testing Self-Driving Trucks

NPR Technology

A mail carrier for the United States Postal Service makes deliveries at a Florida apartment complex in June 2018. The USPS has partnered with TuSimple to launch a multi-state driverless semi-truck test program on Tuesday. It doesn't involve home deliveries. A mail carrier for the United States Postal Service makes deliveries at a Florida apartment complex in June 2018. The USPS has partnered with TuSimple to launch a multi-state driverless semi-truck test program on Tuesday.


AI and machine learning will throw bigger punches at ad fraud

#artificialintelligence

In a poll conducted by Integral Ad Science (IAS) 69.0% of agency executives said that ad fraud was the biggest hindrance to ad budget growth, compared with more than half (52.6%) of brand professionals who said the same. How much is ad fraud costing advertisers? Nobody knows, but with estimates ranging from $6.5 billion to $19 billion, there's a lot at stake. Marketers are becoming more assertive in their demands for better fraud prevention measures and they are seeking to increase their knowledge of different fraud types – from bots to unauthorised domain reselling – and wider technology adoptions to drive their Marketing strategies overall. Ad tech providers will need to adapt their technology and techniques to meet this demand.


AI and machine learning will throw bigger punches at ad fraud

#artificialintelligence

In a poll conducted by Integral Ad Science (IAS) 69.0% of agency executives said that ad fraud was the biggest hindrance to ad budget growth, compared with more than half (52.6%) of brand professionals who said the same. How much is ad fraud costing advertisers? Nobody knows, but with estimates ranging from $6.5 billion to $19 billion, there's a lot at stake. Marketers are becoming more assertive in their demands for better fraud prevention measures and they are seeking to increase their knowledge of different fraud types – from bots to unauthorised domain reselling – and wider technology adoptions to drive their Marketing strategies overall. Ad tech providers will need to adapt their technology and techniques to meet this demand.