  Finding obstacle-free paths in unknown environments is a big navigation issue
for visually impaired people and autonomous robots. Previous works focus on
obstacle avoidance, however they do not have a general view of the environment
they are moving in. New devices based on computer vision systems can help
impaired people to overcome the difficulties of navigating in unknown
environments in safe conditions. In this work it is proposed a combination of
sensors and algorithms that can lead to the building of a navigation system for
visually impaired people. Based on traditional systems that use RGB-D cameras
for obstacle avoidance, it is included and combined the information of a
fish-eye camera, which will give a better understanding of the user's
surroundings. The combination gives robustness and reliability to the system as
well as a wide field of view that allows to obtain many information from the
environment. This combination of sensors is inspired by human vision where the
center of the retina (fovea) provides more accurate information than the
periphery, where humans have a wider field of view. The proposed system is
mounted on a wearable device that provides the obstacle-free zones of the
scene, allowing the planning of trajectories for people guidance.
