November 1, 2012 by Bill Steele
Cornell
researchers have created an autonomous flying robot that is as smart as a bird
when it comes to maneuvering around obstacles. Able to guide itself through forests, tunnels or damaged
buildings, the machine could have tremendous value in search-and-rescue
operations. Small flying machines are already common, and GPS technology
provides guidance. Now, Ashutosh Saxena, assistant professor of computer
science, and his team are tackling the hard part: how to keep the vehicle from
slamming into walls and tree branches. Human controllers can't always react
swiftly enough, and radio signals may not reach everywhere the robot goes. The
test vehicle is a quadrotor, a commercially available flying machine about the
size of a card table with four helicopter rotors. Saxena and his team have
already programmed quadrotors to navigate hallways and stairwells. But in the
wild, current methods aren't accurate enough at large distances to plan a route
around obstacles. Saxena is building on methods he previously developed to turn
a flat video camera image into a 3-D model of the environment using such cues
as converging straight lines, the apparent size of familiar objects and what
objects are in front of or behind each other—the same cues humans unconsciously
use to supplement their stereoscopic vision.
Read more at: http://phys.org/news/2012-11-smart-bird-robot-obstacles.html#jCp
Read more at: http://phys.org/news/2012-11-smart-bird-robot-obstacles.html#jCp
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