  This work describes the implementation of a simple and computationally
efficient Intelligent Navigation System (INS) for autonomous systems used in
areas where human access is impossible. The system uses Laser Range Finder
(LRF) readings as input, making it suitable for mobile platform implementation.
The INS pre-processes the LRF readings to remove noise and determines an
obstacle-free path for mapping. The system's localization method uses a
similarity transform and particle filter. The system was tested in artificially
generated environments and emulated in real-time with real-environment data.
The system was then implemented in a Raspberry Pi3 on a 3WD Omni-directional
mobile platform and tested in real environments. The system was able to
generate an accurate 2D map of the area. The proposed methodology was shown to
be efficient through a comparative analysis of execution time.
