Machine Learning for Modeling Soil-Tool Interactions

When construction equipment digs, this generates a complex set of physical interactions between the machine and the soil. Being able to accurately simulate such interactions in real-time opens the door to improved operator training and even adaptively-tuned digging operation that optimize the energy-efficiency of construction equipment. With recent advanced in artificial intelligence (AI), this is now within reach. Montreal-based CM Labs is already a global leader in simulations for construction vehicles, and this research will expand the features and types of vehicle simulations it offers and thus increase market share. Improving the realism of simulations involving soil also enables entering new engineering design and simulation markets, initially through our current construction equipment OEMs (Original Equipment Manufacturers), generating profits and new hires.

Faculty Supervisor:

Krzysztof Skonieczny

Student:

Amin Haeri

Partner:

CM Labs Simulations

Discipline:

Engineering - computer / electrical

Sector:

Other

University:

Concordia University