Abstract
In this paper, the problem of vision-based autonomous navigation inside buildings is addressed. In our simplified scenario the vehicle navigates along an irregular corridor the shape of which is not known a priori, but is is characterized by boundaries having a simple piecewise-linear profile. The navigation problem is approached as the control problem of tracking the 'mopboard' of one of the walls of the corridor while keeping at a preset distance from it. The state of the system consists in the state of the vehicle augmented by a description of the environment. The environment is sensed using early vision techniques and is modelled as a filtered random walk, as proposed by Dickmanns in his work on road-following. Dickmanns' road model is augmented with a jump-process to handle environment discontinuities. We demonstrate our scheme and compare it to Dickmanns' in extensive simulations.
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