MIT team places sixth at international DARPA Robotics Challenge
CSAIL team just misses winning the grand prize after programming a 400-lb humanoid robot to lift beams, climb stairs, and drive a car.
Gauging materials’ physical properties from video
“Visual microphone” technology could lead to noninvasive identification of objects’ structural defects.
Object recognition for free
System designed to label visual scenes according to type turns out to detect particular objects, too.
Vision system for household robots
New algorithm could enable household robots to better identify objects in cluttered environments.
Five CSAIL researchers named ACM fellows
The Association for Computer Machinery cites Devadas, Grimson, Morris, Rubinfeld, and Rus as having "provided key knowledge" to computing.
Can you out-race a computer?
Deep-learning algorithm can weigh up a neighborhood better than humans.
Fingertip sensor gives robot unprecedented dexterity
Equipped with a novel optical sensor, a robot grasps a USB plug and inserts it into a USB port.
Where to grab space debris
Algorithm tested aboard the International Space Station analyzes the rotation of objects in space.
An end to drug errors?
Mint Solutions tackles medication errors with scanning system that ensures patients get the right pills.
Extracting audio from visual information
Algorithm recovers speech from the vibrations of a potato-chip bag filmed through soundproof glass.
Who did what?
Techniques from natural-language processing enable computers to efficiently search video for actions.
Never forget a face
New algorithm uses subtle changes to make a face more memorable without changing a person’s overall appearance.
Taking a new look at subway map design
CSAIL researchers are using a computational model that better understands peripheral vision to test the usability of MBTA subway maps.
Teaching computers to see — by learning to see like computers
By translating images into the language spoken by object-recognition systems, then translating them back, researchers hope to explain the systems’ failures.