Real-time visual detection for robotic inspection

The project aims to equip Hydro-Québec’s current and future fleet of inspection robots with autonomous inspection capabilities. The three main objectives of the project are:
1. Leverage breakthroughs in artificial intelligence to enable robotic vehicles to realize real-time automated visual inspection of the company’s infrastructure.
2. Facilitate and accelerate deep neural network (DNNs) machine learning through visual simulation and synthetic images.
3. Use a simply and securely deployable robotic vehicle to perform the company’s first fully autonomous power line components inspection missio

Faculty Supervisor:

Yoshua Bengio

Student:

Philippe Lelièvre

Partner:

Hydro-Québec

Discipline:

Computer science

Sector:

Energy

University:

Université de Montréal