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 two 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. A new RoboBee from Harvard can swim underwater, and then launch itself into the air with a microrocket and fly away. At the millimeter scale, the water's surface might as well be a brick wall.
While running a SLAM algorithm, a robot can explore strange terrain, building a map of its surroundings while at the same time positioning, or localizing, itself within that map. Wyeth had long been interested in brain-inspired computing, starting with work on neural networks in the late 1980s. Their aim wasn't to create maps built with costly lidars and high-powered computers--they wanted their system to make sense of space the way animals do. To mimic this structure and behavior in software, Milford adopted a type of artificial neural network called an attractor network.
These autonomous ground robots can be deployed to establish a mobile microgrid. Muscular activity contains information on motion intention. By decoding the muscular activity of an arm during reachig-to-grasp motions, Billard Lab was able to detect grasp type in the early stages of a reaching motion which enables fast activation of a robotic hand by teleoperation. Our goal is to develop AirSim as a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles.
Nuno Vasconcelos, a visual computing expert at the University of California, San Diego, says bikes pose a complex detection problem because they are relatively small, fast and heterogenous. Consider the Deep3DBox algorithm presented recently by researchers at George Mason University and stealth-mode robotic taxi developer Zoox, based in Menlo Park, Calif. On an industry-recognized benchmark test, which challenges vision systems with 2D road images, Deep3DBox identifies 89 percent of cars. More automakers are expected to follow suit as European auto safety regulators begin scoring AEB systems for cyclist detection next year. In December, Wiedenmeier warned that self-driving taxis deployed by Uber Technologies were violating California driving rules designed to protect cyclists from cars and trucks crossing designated bike lanes.
On the stage next to Krafcik stood a self-driving hybrid minivan from Fiat Chrysler equipped with his company's technology. A short-range lidar covers areas beside the minivan that would otherwise have been in the shadow of the rooftop sensor. Exactly how much of Waymo's self-driving prowess comes from such hardware--rather than improved software and road mapping--isn't clear. What is clear is that Waymo wants to supply the entire auto industry with packages that can be fitted to just about any vehicle.
Take a short walk through Singapore's city center and you'll cross a helical bridge modeled on the structure of DNA, pass a science museum shaped like a lotus flower, and end up in a towering grove of artificial Supertrees that pulse with light and sound. It's no surprise, then, that this is the first city to host a fleet of autonomous taxis. Since last April, robo-taxis have been exploring the 6 kilometers of roads that make up Singapore's One-North technology business district, and people here have become used to hailing them through a ride-sharing app. Maybe that's why I'm the only person who seems curious when one of the vehicles--a slightly modified Renault Zoe electric car--pulls up outside of a Starbucks. Seated inside the car are an engineer, a safety driver, and Doug Parker, chief operating officer of nuTonomy, the MIT spinout that's behind the project.
Traffic congestion costs the U.S. economy $121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide emissions, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added. The next step is to have traffic signals talk to cars. Pittsburgh is the test bed for Uber's self-driving cars, and Smith's work on AI-enhanced traffic signals that talk with self-driving cars is paving the way for the ultimately fluid and efficient autonomous intersections.
If evolution is provided with suitable materials in order to devise the morphology of the robot, morphological computation will emerge, characterized by effective and natural-looking behaviors requiring very little active control. At the same time, our results suggest that automated optimization tools such as evolutionary algorithms should be put in place in order to design soft robots, whose effective behavior usually arises from a complex intertwining of different factors, whose complexity can easily become intractable for a human designer. The aim is to give people with little hardware or software experience a platform to get started and learn how autonomous vehicles work. In this video, we applied our Distributed Iterative Learning Control (ILC) approach to a team of four quadrotors.
The FCC filings referenced in the IEEE Spectrum story are not part of our autonomous vehicle development program. This is the first concrete indication of the scale and intended deployment date of GM and Lyft's autonomous on-demand network since GM announced a US 500 million investment in Lyft in January. In late July, however, engineers at General Motors filed applications for thousands of millimeter range radar systems. The 76-GHz radars represent "a new hardware generation", according to a written request to the FCC for confidentiality by Jeffrey Clark, a GM engineer in charge of long range radars.