Using Occupancy Grids for Mobile Robot Perception and Navigation
Alberto ELfes
COMPUTER MAGAZINE
Jun. 1989
Abstract:
This article reviews an approach to
robot perception and world modeling that
uses a probabilistic tesselated representation
of spatial information called the occupancy
grid.’ The occupancy grid is a multidimensional
random field that maintains stochastic estimates
of the occupancy state of the cells in a spatial lattice.
To construct a sensor-derived map of the robot’s world,
the cell state estimates are obtained by interpreting the
incoming range readings using probabilistic sensor models.
Bayesian estimation procedures allow the incremental
updating of the occupancy grid using readings taken
from several sensors over multiple points of view.
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