Untitled Document
|
Not a member yet? Register
for full benefits! |
|
|
|
|
Chaos filter helps robots make sense of the world
This story is from the category Artificial Intelligence
Date posted: 26/02/2009
University of Oxford researchers have come up with a way for map-building robots to accurately recognize places they have been before, even when objects have moved or are approached from a new angle.
Their FabMap software tackles those problems by having a robot assign a visual "vocabulary" of up to a thousand individual "words" for each scene, every two seconds. That means when the robot revisits a scene that now lacks, say, a bicycle, it notes a single change rather than the disappearance of many smaller features. This the robot is more likely to recognise the scene as familiar.
See the full Story via external site: www.newscientist.com
Most recent stories in this category (Artificial Intelligence):
03/03/2017: Application of Fuzzy Logic Teaches Drones to land on Moving Targets
02/03/2017: Poker-playing AI program first to beat pros at no-limit Texas hold 'em
05/02/2017: Google's driverless cars make progress
04/02/2017: Study Exposes Major Flaw in Turing Test
31/01/2017: Artificial intelligence uncovers new insight into biophysics of cancer
31/01/2017: Hungry penguins help keep smart car code safe
12/01/2017: First ever perched landing performed using machine learning algorithms
12/01/2017: AI takes on humans in marathon poker game
|
|