Panoptic segmentation of an underground mine point cloud

Underground mining operations highly depend on accurate information for intelligent decision-making, may it be safety-wise or efficiency-wise. However, the industry still uses old technologies to keep track of the evolution of their mines. This project aims to develop a new technology to help keep mines safer and make operations more efficient using point clouds. Point clouds are a novel means for 3D visualization in which space is mapped through points using specialized scanning equipment. For this project, various algorithms are developed to harness the power of point cloud visualization. The key goal is to identify structures (e.g. ventilation ducts, piping, etc.) in such 3D visualizations, through the use of artificial intelligence.

Faculty Supervisor:

Louis Gosselin

Student:

Partner:

Intelligence industrielle Nemesis;Groupe MISA

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Université Laval

Program: