  Navigation in varied and dynamic indoor environments remains a complex task
for autonomous mobile platforms. Especially when conditions worsen, typical
sensor modalities may fail to operate optimally and subsequently provide inapt
input for safe navigation control. In this study, we present an approach for
the navigation of a dynamic indoor environment with a mobile platform with a
single or several sonar sensors using a layered control system. These sensors
can operate in conditions such as rain, fog, dust, or dirt. The different
control layers, such as collision avoidance and corridor following behavior,
are activated based on acoustic flow queues in the fusion of the sonar images.
The novelty of this work is allowing these sensors to be freely positioned on
the mobile platform and providing the framework for designing the optimal
navigational outcome based on a zoning system around the mobile platform.
Presented in this paper is the acoustic flow model used, as well as the design
of the layered controller. Next to validation in simulation, an implementation
is presented and validated in a real office environment using a real mobile
platform with one, two, or three sonar sensors in real time with 2D navigation.
Multiple sensor layouts were validated in both the simulation and real
experiments to demonstrate that the modular approach for the controller and
sensor fusion works optimally. The results of this work show stable and safe
navigation of indoor environments with dynamic objects.
