  Recently, researchers have been exploring various ways to improve the
effectiveness and efficiency of autonomous vehicles by researching new methods,
especially for indoor scenarios. Autonomous Vehicles in indoor navigation
systems possess many challenges especially the limited accuracy of GPS in
indoor scenarios. Several, robust methods have been explored for autonomous
vehicles in indoor scenarios to solve this problem, but the ineffectiveness of
the proposed methods is the high deployment cost. To address the
above-mentioned problems we have presented A low-cost indoor navigation method
for autonomous vehicles called Affordable Indoor Navigation Solution (AINS)
which is based on based on Monocular Camera. Our proposed solution is mainly
based on a mono camera without relying on various huge or power-inefficient
sensors to find the path, such as range finders and other navigation sensors.
Our proposed method shows that we can deploy autonomous vehicles indoor
navigation systems while taking into consideration the cost. We can observe
that the results shown by our solution are better than existing solutions and
we can reduce the estimated error and time consumption.
