Watch: MIT Drone Autonomously Avoids Obstacles at 30 MPH

As reported by Robotics Trends: Obstacle avoidance needs to be the next big thing for drones. As 3D Robotics founder Chris Anderson said, the “mass jackassery” (reckless flying) needs to stop. It’s part of the reason we now have a mandatory drone registration system looming over us.

DJI has been on the forefront of avoidance technology for drones, recently introducing its Guidance system that uses multiple stereo and ultrasonic sensors that allows the drone to automatically avoid obstacles within 65 feet.

Andrew Barry, a PhD student at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), is looking to push this technology to the next level. Barry and professor Russ Tedrake have created an obstacle-detection system that allows a drone to autonomously avoid obstacles in its flight path while flying 30 miles per hour.

CSAIL posted a fascinating video, which you can watch below, of Barry’s system helping a drone “dip, dart and dive” through a tree-filled field.

The drone in the video, which was made with off-the-shelf components for $1,700, weighs just over a pound and has a 34-inch wingspan. It has a camera on each wing and two processors that are “no fancier than the ones you’d find on a cellphone.”

CSAIL says Barry’s software runs 20 times faster than existing obstacle detection software. Operating at 120 frames per second, the open-source software allows the drone to detect objects and map its environment in real time, extracting depth information at 8.3 milliseconds per frame.

“Sensors like lidar are too heavy to put on small aircraft, and creating maps of the environment in advance isn’t practical,” Barry says. “If we want drones that can fly quickly and navigate in the real world, we need better, faster algorithms.”

So, how does it work? We’ll let CSAIL explain:

Traditional algorithms focused on this problem would use the images captured by each camera, and search through the depth-field at multiple distances - 1 meter, 2 meters, 3 meters, and so on - to determine if an object is in the drone’s path.

Such approaches, however, are computationally intensive, meaning that the drone cannot fly any faster than 5 or 6 miles per hour without specialized processing hardware.

Barry’s realization was that, at the fast speeds that his drone could travel, the world simply does not change much between frames. Because of that, he could get away with computing just a small subset of measurements - specifically, distances of 10 meters away.

“You don’t have to know about anything that’s closer or further than that,” Barry says. “As you fly, you push that 10-meter horizon forward, and, as long as your first 10 meters are clear, you can build a full map of the world around you.”

While such a method might seem limiting, the software can quickly recover the missing depth information by integrating results from the drone’s odometry and previous distances.

Barry wrote about the system in his paper “Pushbroom Stereo for High-Speed Navigation in Cluttered Environments” (PDF) and says he needs to improve the software so it can work at more than one depth and dense environments.

“Our current approach results in occasional incorrect estimates known as ‘drift,’” he says. “As hardware advances allow for more complex computation, we will be able to search at multiple depths and therefore check and correct our estimates. This lets us make our algorithms more aggressive, even in environments with larger numbers of obstacles.”

Skreemr Jet Could Fly New York to London in 30 Minutes

As reported by Condé Nast Traveler: There's a lot of excitement around the idea of supersonic travel right now. Airbus has patent approval for a reboot of the Concorde—the Concorde-2—that would go Mach 4 (or faster) to get you from New York to London in an hour. Now designer Charles Bombardier is talking about cutting that travel time in half: with the Skreemr supersonic jet. Allow me to get technical for a second: The Skreemer vision, which looks like a prop from the upcoming Star Wars movie, would launch from a magnetic railgun at Mach 4, ignite rockets to the point where it's going fast enough to "fire up a scramjet," propelling it to a crazy Mach 10, or or 7,673 miles per hour. Popular Mechanics has the full breakdown, but yes, apparently, this could be a passenger jet. (Popular Mechanics)

Starship Technologies Plans to Bring a Fleet of Delivery Drones to the Streets

As reported by Design Boom: formed by skype co-founders, starship technologies is a european startup planning on building a fleet of self-driving delivery drones made to transport goods locally within 30 minutes. designed using readily available components, the robots are lightweight and low-cost, enabling the company to bring the current cost of delivery down by 10 to 15 times per shipment.

the fleet will reduce CO2 emissions, and will create unprecedented convenience for individuals while opening up new opportunities for businesses such as parcel firms or grocery stores. the robots are intended to slip seamlessly into the environment, traveling at slow speeds on sidewalks blending safely in with pedestrian traffic. starship technologies are currently testing and demonstrating prototypes and plans to launch the first pilot services in cooperation with its partners in the US, UK and other countries in 2016.

‘our vision revolves around three zeroes – zero cost, zero waiting time and zero environmental impact,’ explains ahti heinla, a skype co-founder and CEO at starship technologies. ‘we want to do to local deliveries what skype did to telecommunications. with e-commerce continuing to grow consumers expect to have more convenient options for delivery – but at a cost that suits them. the last few miles often amounts to the majority of the total delivery cost. our robots are purposely designed using the technologies made affordable by mobile phones and tablets – it’s fit for purpose, and allows for the cost savings to be passed on to the customer.’

The drones will travel on sidewalks at about 4 miles per hour for package weights of up to 20 lbs.  The top lid opens to fit small and medium sized packages and the unit is opened through the use of an app on the customer's smartphone.  The units can also be tracked by the deliverer or the customer.

Starship's robots are said to be "99-percent" autonomous, which means that although they'll drive themselves, human oversight will be present at all times, ready to take control if the robot gets confused.

Starship Technologies is clearly targeting companies that want to compete with services like Amazon's Prime Now one-hour deliveries -- although there's no reason why Amazon couldn't integrate this robot into its supply chain if it proves as cost-effective as claimed. The company still has a lot of questions to answer, though. It says the robots "consume less energy than most light bulbs," but that's not exactly the most precise metric. We also don't know how much it'll cost companies to run and maintain a fleet of bots, or whether Starship can secure the necessary regulatory permission to ride on sidewalks. Assuming it can answer those questions, and the many more that'll arise in the coming months, Starship says it'll launch "pilot services" in partnership with other companies across the US, UK, and other countries in 2016.

Cars That Talk to Each Other Could Be Easier to Hack and Track

Chatty cars make it easier for eavesdroppers.

As reported by Slate: Digitially connecting cars to each other and to highway infrastructure promises to drastically reduce collisions and traffic jams. But that wireless vehicular chatter comes at a cost to your privacy: A car that never shuts up may be a lot easier to track.

Researchers at the Universities of Twente in the Netherlands and Ulm in Germany have found that they can use just a few thousands of dollars’ worth of equipment to track a vehicle that’s emitting the so-called “connected vehicle” wireless communications proposed for future vehicle-to-vehicle (V2V) connections.

With only two $550 devices strategically planted at intersections on the University of Twente’s 432-acre campus, they were able to follow unique signatures in cars’ radio communications, predicting which of two campus regions the vehicle was in with 78 percent accuracy, as well as the car’s more precise location on a specific road with 40 percent accuracy. Extrapolating from that proof-of-concept, the researchers believe that the same technique, expanded with a few hundred thousand dollars of hardware, could be used by governments or even amateurs to monitor vehicles over an entire small city.

“The vehicle is saying ‘I’m Alice, this is my location, this is my speed and my direction.’ Everyone around you can listen to that,” says Jonathan Petit, one of the authors of the study, which will be presented at the Black Hat Europe security conference next month and was first reported by IEEE Spectrum. “They can say, ‘there’s Alice, she claimed she was at home, but she drove by the drug store, went to a fertility clinic,” this kind of thing … Someone can infer a lot of private information about the passenger.”

The proposed connected car protocol, which the National Highway Traffic and Safety Administration (NHTSA) will consider mandating for the first time in American cars in 2017, uses the Wi-Fi-like 802.11p wireless signal and could allow cars to communicate with both each other and with highway infrastructure like roads or bridges. One NHTSA study in 2010 estimated that the protocol could prevent as many as 81 percent of all vehicle collisions.

But Petit, one of the University of Twente researchers, says that with the range of that wireless communication falling between roughly 300 and 900 feet, it could also serve as a powerful surveillance mechanism. It’s not yet clear how often connected vehicles will vary the unique wireless signatures that identify them, which could limit their use for tracking an individual car. But depending on how long those “pseudonyms” remain constant, Petit argues the connected vehicle protocol could offer a new, relatively cheap form of vehicle tracking that could bolster existing law enforcement tracking techniques like automatic license plate readers. Or, he imagines, hackers could collect and crowdsource data from the system to assemble a database of vehicle movements around entire cities.

“When you do a deployment like this, you need to think about privacy,” says Petit. “It was clear that we needed to perform this attack, to demonstrate that this information is accessible to anyone.”

For their proof-of-concept, the researchers used two Cohda Wireless MK3 radio modules and attached a pair of Smarteq antennae to each one, at a total cost of about $1,100 dollars. With those modules located at two intersections on the Twente campus, they could roughly track a vehicle that contained an active Nexcom 802.11p radio beacon. The graphs below show the location of the intersections where those two modules were planted and a “privacy heat map” of how accurately the researchers could predict a car’s location based on the resulting radio readings.

Wired

Though their two modules only gave them about a 40 percent chance of locating the vehicle at any given time down to a 65 foot area, the researchers extrapolated that a few more modules could give them much more precision. Each added radio module at an intersection offers more information about where a target car has been spotted and which direction it’s turned at a given time. If the researchers were to cover eight of the campus’ 21 intersections (at a cost of $4,400 dollars), for instance, they believe they could predict the location of the target vehicle with 90 percent accuracy.

In their paper, the researchers calculate that they could extend that surveillance to an entire city for less than half a million dollars. They write that the system could cover the nearby Dutch city of Enschede, for instance, with more than 150,000 people and 35,200 acres of land, for around $362,000. And they believe that their “sniffing stations” could easily drop in price—they even speculate that one could likely soon be built for a tenth of the cost using a Raspberry Pi minicomputer—to vastly cut the cost of that tracking. “If you have sufficient coverage of a city, you can track everyone,” Petit says.

Programming vehicles to switch their unique radio signatures more often could alleviate some of those privacy concerns, Petit notes. And Petit acknowledges that industry groups like the Crash Avoidance Metrics Partnership in the US and the Car-2-Car Consortium in Europe are considering that privacy fix. (Neither organization immediately responded to Wired’s request for comment.)

But Petit says more study is needed to understand exactly how much those pseudonym protections can foil tracking. With a high enough density of tracking modules, the researchers caution that someone could overcome even rapid pseudonym-switching to pervasively follow vehicles’ whereabouts. The chart below shows how often the researchers calculate that they could predict the location of a vehicle given different numbers of tracking modules and different lengths of time between vehicle pseudonym changes. (A “privacy score” of 1 means no chance of a vehicle being identified, and a zero means 100 percent certainty of identifying it.)

Wired

Even so, Petit argues that graph should still be evidence that the pseudonym-switching strategy needs to be built into car-to-car communication systems. Though rapidly changing the vehicle’s signature can’t combat some sort of “global observer,” he says, it can still block cheaper, lower resource types of surveillance.

“Pseudonym changing doesn’t stop tracking. It can only mitigate this attack,” says Petit. “But it’s still needed to improve privacy against this mid-size observer…We want to demonstrate that in any deployment, you still have to have this protection, or someone will be able to track you.”

Watch Tesla's Autopilot Stop an Uber Driver's Head-On Collision

As reported by Fortune: The “look Ma, no hands” approach just paid off big time.

How do you narrowly avoid a nasty car crash without even touching the steering wheel or the brakes? Lucky for one Uber driver, his ride is a Tesla.

On a recent rainy and pitch-black morning in Seattle, Jon Hall had just dropped off a passenger and was cruising along the highway in his Tesla at nearly 45 mph when another car made a sharp U-turn in front of him, cutting him off. But Hall was using Tesla’s new autopilot feature, and his electric vehicle stopped immediately, saving him and his self-driving car from a potentially fatal head-on collision.

“I wasn’t even able to honk the horn before the car came to a stop,” Hall wrote in an online discussion of the video of the incident, which he posted on YouTube, saying, “I did not touch the brake. Car did all the work.”

The video was captured on Hall’s dashboard camera, though it does not include sound because he had disabled audio while driving Uber passengers in order to comply with Washington privacy laws. (“I screamed, honked, and yelled,” he explains.) Watch the full video of the autonomous vehicle’s feat here:

Air Force Set to Launch Next-to-Last GPS IIF Satellite

As reported by Wireless Design Mag: Air Force Space Command's Space and Missile Systems Center and its mission partners are scheduled to launch the 11th Boeing-built Global Positioning System IIF satellite aboard a United Launch Alliance Atlas V 401 launch vehicle Oct. 30 from Space Launch Complex 41 at Cape Canaveral Air Force Station, Florida.

The launch window is set to open at 12:17 p.m. EDT and will remain open for 19 minutes.

Ten GPS IIF satellites are currently on-orbit and meeting all mission requirements. Of the remaining satellites, GPS IIF-11 is awaiting launch and GPS IIF-12, the remaining IIF-series satellite, is in storage awaiting final processing and preparation for a Feb. 3 launch.

GPS IIF satellites provide improved signals that will enhance the precise global positioning, navigation and timing services supporting both the warfighter and the growing civilian needs of our global economy. GPS IIF provides improved navigational accuracy through advanced atomic clocks, a longer design life than previous GPS satellites, and a third operational civil signal -- L5 -- that benefits commercial aviation and safety-of-life applications.

"The GPS IIF satellites play a key role in our modernization effort to provide new space-based capabilities for users around the globe and for decades to come," said Lt. Gen. Samuel Greaves, the Space and Missile Systems Center commander and Air Force program executive officer for space. "We have successfully placed into operation 10 in a series of 12 procured Boeing-built space vehicles, and thanks to the exceptional team of government, industry and launch personnel we are poised to launch the 11th GPS IIF satellite aboard an Atlas V 401 launch vehicle later this week.”

Operated by AFSPC's 50th Space Wing at Schriever Air Force Base, located east of Colorado Springs, Colorado, the GPS constellation provides precise positioning, navigation and timing services worldwide seven days a week, 24 hours a day.

SMC, located at Los Angeles AFB in El Segundo, California, is the Air Force's center of acquisition excellence for acquiring and developing military space systems. Its portfolio includes the Global Positioning System, military satellite communications, defense meteorological satellites, space launch and range systems, satellite control networks, space based infrared systems, and space situational awareness capabilities.

Why Tesla’s Autopilot and Google’s Car are Entirely Different Animals

As reported by RoboHub: In the buzz over the Tesla autopilot update, a lot of commentary has appeared comparing this Autopilot with Google’s car effort and other efforts and what I would call a “real” robocar — one that can operate unmanned or with a passenger who is not paying attention to the road. We’ve seen claims that “Tesla has beaten Google to the punch,” but while the Tesla release is a worthwhile step forward, the two should not be confused as all that similar.

Tesla’s autopilot isn’t even particularly new. Several car makers have had similar products in their labs for several years, and some have released it to the public, at first in a “traffic jam assist” mode, but reportedly in full highway cruise mode outside the USA. The first companies to announce it were Cadillac with the “Super Cruise” and VW’s “Temporary Autopilot” — but they delayed that until much later.

Remarkably, Honda showed off a car ten years ago doing this sort of basic autopilot (without lane change) and sold only in the UK. They decided to discontinue the project, however. That this was actually promoted as an active product ten years ago will give you some clue as to how different this was from the bigger efforts.

Cruise products like these require constant human supervision. With regular cruise control, you could take your feet off the pedals, but might have to intervene fairly often either by using the speed adjust buttons or full control. Interventions could be several times a minute. Later came “Adaptive Cruise Control”, which still required you to steer and fully supervise, but would rarely require intervention on the pedals while driving on the highway — a few times an hour might be acceptable.

The new autopilot systems allow you to take your hands off the wheel but demand full attention. Users report needing to intervene rarely on some highways, but frequently on other roads. Once again, if you only need to intervene once an hour, the product could make your drive more relaxing.

Now consider a car that drives without supervision …

Human drivers have minor accidents about every 2,500 to 6,000 hours, depending on what figures you are using — that would be about once every 10 to 20 years of driving. A fatal accident takes place every 2,000,000 hours of driving — about once every 10,000 years for the typical driver, thankfully a much longer span than a person’s lifetime.

If a full robocar needs human intervention, logic tells you that it’s going to have an accident because there is nobody there to intervene. Just like with human drivers, most of the errors that would cause an accident are minor: running off the road, fender benders. Not every mistake that could cause a crash or a fatality causes one. Indeed, humans make mistakes that might cause a fatality far more often than every 2,000,000 hours, because we “get away” with many of them.

Even so, the difference is staggering. A cruise autopilot (such as Tesla’s) is a workable product if you have to correct it a few times an hour, whereas a full robocar product is only workable if you need to correct it only after decades or even lifetimes of driving. This is not a difference of degree, it is a difference of kind. It is why there is probably not an evolutionary path from the cruise/autopilot systems based on existing ADAS technologies to a real robocar. Doing many thousands times better will not be done by incremental improvement. It almost surely requires a radically different approach, and probably very different sensors.

To top it all off, a full robocar doesn’t just need to be great at avoiding accidents. If it’s running unmanned, with no human to help it at all, it needs a lot of other features and capabilities too.

The mistaken belief in an evolutionary path also explains why some people imagine robocars are many decades away. If you wanted evolutionary approaches to take you to 100,000x better, you would expect to wait a long time. When an entirely different approach is required, what you learn from the old approach doesn’t help you predict how the other approaches — including unknown ones — will do.

It does teach you something, though. By simply being on the road, Tesla will encounter all sorts of interesting situations its developers weren’t expecting, and they will use this data to train new generations of software that do better. They will learn things that help them make the revolutionary unmanned product they hope to build in the 2020s. This is a good thing.

Google and others have also been out learning that, and soon more teams will.