In a leap for robot development, the Massachusetts Institute of Technology researchers who built a robotic cheetah have now trained it to see and jump over hurdles as it runs, making this the first four-legged robot to run and jump over obstacles autonomously. To get a running jump, the robot plans out its path, much like a human runner: As it detects an approaching obstacle, it estimates that object’s height and distance.
What if handheld tools know what needs to be done and were even able to guide and help...
Today’s industrial robots are remarkably efficient, as long as they’re in a controlled...
Using a smart tablet and a red beam of light, Georgia Institute of Technology researchers have created a system that allows people to control a fleet of robots with the swipe of a finger. A person taps the tablet to control where the beam of light appears on a floor. The swarm robots then roll toward the illumination, constantly communicating with each other and deciding how to evenly cover the lit area.
In what marks a significant step forward for artificial intelligence, researchers at Univ. of California, Santa Barbara, have demonstrated the functionality of a simple artificial neural circuit. For the first time, a circuit of about 100 artificial synapses was proved to perform a simple version of a typical human task: image classification.
For the last decade, scientists have deployed increasingly capable underwater robots to map and monitor pockets of the ocean to track the health of fisheries, and survey marine habitats and species. In general, such robots are effective at carrying out low-level tasks, specifically assigned to them by human engineers, a tedious and time-consuming process for the engineers.
Researchers studying how the brain makes decisions have, for the first time, recorded the moment-by-moment fluctuations in brain signals that occur when a monkey making free choices has a change of mind. The findings result from experiments led by electrical engineering Prof. Krishna Shenoy, whose Stanford Univ. lab focuses on movement control and neural prostheses controlled by the user's brain.
Computer scientists at the Univ. of California, San Diego, have combined sophisticated computer vision algorithms and a brain-computer interface to find mines in sonar images of the ocean floor. The study shows that the new method speeds detection up considerably, when compared to existing methods, which mainly consist of visual inspection by a mine detection expert.
Most people are naturally adept at reading facial expressions to tell what others are feeling. Now scientists have developed ultra-sensitive, wearable sensors that can do the same thing. Their technology, reported in the ACS Nano, could help robot developers make their machines more human.
Most recent advances in artificial intelligence are the result of machine learning, in which computers are turned loose on huge data sets to look for patterns. To make machine-learning applications easier to build, computer scientists have begun developing so-called probabilistic programming languages, which let researchers mix and match machine-learning techniques that have worked well in other contexts.
Many studies show that video gamers perform better than non-gamers on certain visual tasks, like managing distractors and identifying targets, but a small new Brown Univ. study provides gamers with some cognitive bonus points. The study results suggest that gaming not only improves their visual skill but also may improve their learning ability for those skills.
Researchers at Carnegie Mellon Univ. (CMU) who develop snake-like robots have picked up a few tricks from real sidewinder rattlesnakes on how to make rapid and even sharp turns with their undulating, modular device. Working with colleagues at the Georgia Institute of Technology and Zoo Atlanta, they have analyzed the motions of sidewinders and tested their observations on CMU’s snake robots.
The most realistic risks about the dangers of artificial intelligence are basic mistakes, breakdowns and cyber attacks, an expert in the field says—more so than machines that become super powerful, run amok and try to destroy the human race.
Researchers from Brown and Johns Hopkins have come up with a new way to evaluate how well computers can divine information from images. The team describes its new system as a “visual Turing test,” after the legendary computer scientist Alan Turing’s test of the extent to which computers display human-like intelligence.
With the most unpredictable U.K. general election looming in modern times, how can big data be used to understand how elections are covered by the media? New research has, for the first time, analyzed over 130,000 online news articles to find out how the 2012 U.S. presidential election played out in the media.
Ninety percent of automobile accidents involve human error. If scientists succeed in producing computer-driven cars, responsibility may shift to programming errors. In that case, who sues whom? Who is liable?
Researchers building a new underwater robot they’ve dubbed the “Millennium Falcon” certainly have reason to believe it will live up to its name. The robot will deploy instruments to gather information in unprecedented detail about how marine life interacts with underwater equipment used to harvest wave and tidal energy.
People typically consider doing the laundry to be a boring chore. But laundry is far from boring for artificial intelligence (AI) researchers. To AI experts, programming a robot to do the laundry represents a challenging planning problem because current sensing and manipulation technology is not good enough to identify precisely the number of clothing pieces that are in a pile and the number that are picked up with each grasp.
Scientists have developed an octopus-like robot, which can zoom through water with ultra-fast propulsion and acceleration never before seen in man-made underwater vehicles. Most fast aquatic animals are sleek and slender to help them move easily through the water but cephalopods, such as the octopus, are capable of high-speed escapes by filling their bodies with water and then quickly expelling it to dart away.
When disaster strikes, it's important for responders and emergency officials to know what critical infrastructure has been damaged so they can direct supplies and resources accordingly. Doug Stow, a geography professor from San Diego State Univ., is developing a program that uses before-and-after aerial imagery to reveal infrastructure damage in a matter of minutes.
For decades, researchers in artificial intelligence, or AI, worked on specialized problems, developing theoretical concepts and workable algorithms for various aspects of the field. Computer vision, planning and reasoning experts all struggled independently in areas that many thought would be easy to solve, but which proved incredibly difficult.
Much of our reams of data sit in large databases of unstructured text. Finding insights among emails, text documents and Websites is extremely difficult unless we can search, characterize and classify their text data in a meaningful way. One of the leading big data algorithms for finding related topics within unstructured text (an area called topic modeling) is latent Dirichlet allocation (LDA).
Every undergraduate computer science major takes a course on data structures, which describes different ways of organizing data in a computer’s memory. Every data structure has its own advantages: Some are good for fast retrieval, some for efficient search, some for quick insertions and deletions and so on. Today, hardware manufacturers are making computer chips faster by giving them more cores, or processing units.
A device, possibly an unmanned aerial drone, was found on the White House grounds during the middle of the night while President Barack Obama and the first lady were in India, but his spokesman said today that it posed no threat. It was unclear whether their daughters, Sasha and Malia, were at home at the time of the incident with their grandmother, Marian Robinson, who also lives at the White House.
Optimization algorithms are everywhere in engineering. Among other things, they’re used to evaluate design tradeoffs, to assess control systems and to find patterns in data. One way to solve a difficult optimization problem is to first reduce it to a related but much simpler problem, then gradually add complexity back in, solving each new problem in turn and using its solution as a guide to solving the next one.
Acute care nurse practitioner students, specializing in flight nursing at Case Western Reserve Univ., will soon be training in the nation’s first state-of-the-art simulator built in an actual helicopter. The simulator creates the sense of treating critically injured patients from takeoff to landing. The helicopter simulator was installed at the university’s Cedar Avenue Service Center.
The stars are aligning for science and engineering, as a new movie about a high school robotics team makes its debut in theaters nationwide. The movie, “Spare Parts,” is based on FIRST Robotics Competition Team 842 - Falcon Robotics, from Carl Hayden Community High School in Phoenix, Ariz., and their famous robotic underdog victory against MIT which was chronicled in the WIRED article “La Vida Robot” in 2005.
For household robots ever to be practical, they’ll need to be able to recognize the objects they’re supposed to manipulate. But while object recognition is a highly studied topic in artificial intelligence, even the best object detectors still fail much of the time. Researchers at MIT believe that household robots should take advantage of their mobility and their relatively static environments to make object recognition easier.
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