Vision Based Navigation for a Mobile Robot with Different Field of Views

TL;DR

This paper investigates how varying the field of view (FOV) affects the evolution of vision-based navigation in mobile robots, identifying optimal FOV values for efficient evolution and navigation performance.

Contribution

It systematically evaluates the impact of different FOVs on robot navigation evolution, proposing optimal FOV values for improved efficiency and performance.

Findings

Optimal FOV reduces the number of generations needed for evolution.

Robots with optimal FOV navigate more effectively.

FOV significantly influences the evolution process and navigation success.

Abstract

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.