  The basic idea behind evolutionary robotics is to evolve a set of neural
controllers for a particular task at hand. It involves use of various input
parameters such as infrared sensors, light sensors and vision based methods.
This paper aims to explore the evolution of vision based navigation in a mobile
robot. It discusses in detail the effect of different field of views for a
mobile robot. The individuals have been evolved using different FOV values and
the results have been recorded and analyzed.The optimum values for FOV have
been proposed after evaluating more than 100 different values. It has been
observed that the optimum FOV value requires lesser number of generations for
evolution and the mobile robot trained with that particular value is able to
navigate well in the environment.
