Robots






The Morning After: Apple HomePod, reviewed

Engadget

Hey, good morning! You look fabulous. Happy Valentine's Day! Now that's out of the way, we've got Apple's HomePod review (great sound, not so smart), adorable robot skiers and problems with Star Trek Discovery. The company's first smart speaker sounds great, but is that enough? Apple HomePod revie...


Robots had their own skiing competition at the Winter Olympics

Engadget

The Olympics aren't just an event for the most talented athletes to strut their stuff on the world's stage. No, The Games are where robots can find honest work and leisure, too. Some 85 robots (spread across 11 different models, humanoid and otherwise) have been serving drinks, cleaning floors, swimming around fish tanks, guiding lost visitors at the airport and even skiing according to regional publication Korea JoongAng Daily. "We applied three yardsticks in choosing the robots to use at The Games -- how stable, new and useful they are going to be," Park Hyun-Sub, of the Korea Advanced Institute of Science and Technology said. The robot skiing competition was held yesterday at an event adjacent to the Olympic village. According to The Guardian, each bot had to meet a strict set of criteria to compete. Specifically, they had to be over 50cm tall, have independent power systems, be able to stand on two legs and have bendable knees and elbows. Oh, they need to use skis and poles, obviously. "Sensors enabled the robots to detect the position of flags on the course, which they had to steer themselves through," the publication writes. "Points were awarded for the number of flagpoles avoided, and the fastest time to the finish line. Not that all of the robots reached it." Sounds familiar. For a glimpse at the action, check out the video below. Couldn't make it to South Korea this year to see this in action for yourself? Japan says it's going to double down on robots when it hosts the Olympics in 2020.


The Skydio R1 might be the smartest consumer drone in the sky

Engadget

Autonomous features in commercially available drones are nothing new. Heck, I'm old enough to remember when DJI Phantoms didn't even offer follow-along technology. Shorter version: Most every drone worth its rotors possesses some level of autonomy. But then there's Skydio's R1, which ratchets things...


Boston Dynamics' robots are the politest 'pets' you'll meet

Engadget

We hope you weren't planning on sleeping tonight. Boston Dynamics has posted a video showing that its SpotMini robot can hold the door open for its fellow automatons. If one bot needs a helping hand, it'll signal to another machine nearby that can pry the door open and let it through. It's very polite... and more than a little unsettling, especially since it's not clear they'll extend the same courtesy to humans. At least the robots will have manners when they take over. If you're a tad more trusting, this is good news. Robots have typically only had limited cooperation with each other, and this hints at more advanced team-ups where robots can supplement each others' abilities and accomplish more than they would by themselves. That could be helpful for search and rescue missions, or any situation where it would be impractical to equip every robot with the same features. It's a positive move -- so long as the robots remain friendly.


Play giant-sized 'Pong' by shuffling your feet

Engadget

You may have seen attempts at real-world Pong before, but rarely have they been so... athletic. Moment Factory has created GRiD, a Pong variant that uses a LiDAR sensor (the same tech as in self-driving cars) to create an enormous, 40-by-60 foot playing field where the paddle only moves when you and a partner shuffle your feet together. You could get quite the workout if the teams are evenly matched, and that's before the game adds wrinkles like surprise acceleration or an extra ball. The aim was to bring back the social dimension of games you might remember from the glory days of arcades, when you'd play with strangers that exist as more than an online nickname. GRiD takes it a step further by placing the game in the real world. Moment Factory describes this as the first "prototype" in a series of arcade-related projects. You probably won't see it made widely available, at least not until there's some refinement. All the same, this illustrates just how public gaming experiences can work without requiring VR or other technologies that take you out of the real world.


MIT CSAIL's drone is never quite sure where it is

Engadget

The current generation of autonomous drone navigation and flightpath planning systems are almost too precise, demanding hundreds of measurements be taken so that the UAV knows exactly where it is in space at any given moment. And if those readings are off by even a little, then the drone is in for an impact. What's more, all that data collection is computationally intensive -- especially for smaller drones where the space and weight capacities are limited. The new NanoMap system from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), however, strikes the right balance between accuracy and speed. With it, drones can navigate heavily populated areas -- think forests or Amazon fulfillment centers -- at up to 20 mph. Simply put, the system doesn't sweat the details. Unlike other common mapping systems, such as simultaneous localization and mapping (SLAM), which are data intensive and difficult to maintain at real-time, the NanoMap uses depth-sensing to measure just the drone's immediate surroundings. This enables the drone to understand generally where it is in relation to obstacles and anticipate how it will need to change course to avoid them. "The key difference to previous work is that the researchers created a map consisting of a set of images with their position uncertainty rather than just a set of images and their positions and orientation," says Sebastian Scherer, a systems scientist at Carnegie Mellon University's Robotics Institute, wrote in an MIT release. "Keeping track of the uncertainty has the advantage of allowing the use of previous images even if the robot doesn't know exactly where it is and allows in improved planning." This uncertainty is surprisingly helpful. Without working the factor into its modeling, MIT's test drone would crash roughly 25 percent of the time whenever it drifted more than 5 percent away from where it expected to be. But by incorporating that uncertainty, the MIT team was able to reduce crashes to just 2 percent of its flights.