Active/dynamic stereo vision

Visual navigation is a challenging issue in automated
robot control. In many robot applications, like object manipulation
in hazardous environments or autonomous locomotion, it is
necessary to automatically detect and avoid obstacles while planning
a safe trajectory. In this context the detection of corridors of
free space along the robot trajectory is a very important capability
which requires nontrivial visual processing. In most cases it is
possible to take advantage of the active control of the cameras.
In this paper we propose a cooperative schema in which motion
and stereo vision are used to infer scene structure and determine
free space areas. Binocular disparity, computed on several
stereo images over time, is combined with optical flow from
the same sequence to obtain a relative-depth map of the scene.
Both the time-to-impact and depth scaled by the distance of the
camera from the fixation point in space are considered as good,
relative measurements which are based on the viewer, but centered
on the environment.The need for calibrated parameters is considerably reduced by
using an active control strategy. The cameras track a point in
space independently of the robot motion and the full rotation of
the head, which includes the unknown robot motion, is derived
from binocular image data.The feasibility of the approach in real robotic applications is
demonstrated by several experiments performed on real image
data acquired from an autonomous vehicle and a prototype camera
head.