Lifelong learning for service robots

Traditionally, software for home products could not be changed once they were shipped. Furthermore, they could not run complex machine learning (ML) models because their computing and storage capacities are limited due to budget constraints. Recent advancements of cloud infrastructure, however, may allow such products to collect a large amount of data and continuously update the software system throughout their lifetime. Lifelong learning can potentially improve the user experience by making the software system more intelligent and adaptive to specific user preferences. On the other hand, we need to solve problems such as incremental learning, data representation, and catastrophic forgetting. There may also be security and privacy issues associated with processing user data on the cloud.

Faculty Supervisor:

Animesh Garg

Student:

Partner:

Bosch

Discipline:

Computer science

Sector:

Wholesale trade

University:

University of Toronto

Program: