Robust obstacle avoidance system for visually impaired persons

There is a large number of visually impaired people all over the world according to the World Health Organization. It reduces their mobility significantly as they may bump into obstacles. Robust real-time obstacle avoidance would be very helpful to increase their mobility. The main objective of this project is to develop a robust and fast obstacle avoidance system based on continuous real-time image analysis and deep learning techniques. The proposed system can be installed in assistive systems such wheelchairs or in wearable systems such as smart glasses. The obstacle warning can be given in the form audio feedback or by other appropriate methods.

Faculty Supervisor:

Mrinal Mandal

Student:

Partner:

Clinisys EMR Inc.

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program: