In this chapter, we address the competent Autonomous Vehicles should
have the ability to analyze the structure and unstructured environments
and then to localize itself relative to surrounding things, where GPS,
RFID or other similar means cannot give enough information about the
location. Reliable SLAM is the most basic prerequisite for any further
artificial intelligent tasks of an autonomous mobile robots. The goal of
this paper is to simulate a SLAM process on the advanced software
development. The model represents the system itself, whereas the
simulation represents the operation of the system over time. And the
software architecture will help us to focus our work to realize our wish
with least trivial work. It is an open-source meta-operating system,
which provides us tremendous tools for robotics related problems.

Specifically, we address the advanced vehicles should have the ability
to analyze the structured and unstructured environment based on solving
the search-based planning and then we move to discuss interested in
reinforcement learning-based model to optimal trajectory in order to
apply to autonomous systems.