Development of a Store-and-Forward Navigation System with Semantic Void Detection for Autonomous Construction Monitoring

Current methods for tracking construction progress rely on manual inspections, which are slow, inconsistent, and often dangerous. This research project aims to automate this process using an agile quadruped robot (a “robot dog”) developed by Noûs Technologies. The interns will create a smart navigation system that uses the building’s digital blueprints to guide the robot, ensuring it inspects critical structures like walls and columns. To overcome the limited computer power available on small robots, the team is developing a unique “feedback loop”: the robot records data, a powerful central computer analyzes it to detect any missing spots, and then automatically updates the robot’s plan to capture those gaps the next day. This innovation enables Noûs Technologies to offer a highly accurate, autonomous 3D monitoring service that helps construction companies reduce costly errors and keep projects on schedule.

Faculty Supervisor:

François Ferland

Student:

Partner:

Noûs Technologies

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

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