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Multi-sensor object detection and localization for inspection robots
Hydro-Québec faces numerous challenges to inspect and maintain its infrastructures. Robotics used for infrastructure inspection can lead valuable gains in efficiency. However, large-scale adoption of inspection robots requires higher autonomy levels, like the capacity to autonomously inspect specific assets. AI-based object detection and localization is a key capability to complete autonomous inspections with robots. This project is about leveraging inspection capabilities of inspection robots with deep learning techniques.
Faculty Supervisor:
Ioannis Mitliagkas
Student:
Partner:
Hydro-Quebec (Varennes, QC)
Discipline:
Computer science
Sector:
Utilities
University:
Université de Montréal
Program:
Accelerate
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