Exploiting Experiences and Priors in Semantic Visual Navigation

This fundamental research project investigates semantic visual navigation tasks, such as asking a household robot to “go find my keys”. We seek to enhance the efficacy of repeated search tasks within the same environment, by explicitly building, maintaining, and exploiting a map of locations that the robot had previously explored. We also seek to exploit prior location-tolocation, object-within-location, and object-to-object relationships from similar environments (e.g. within a common cultural region) to improve semantic visual navigation in unseen environments. These advances will benefit the partner organization’s fundamental scientific research efforts, as well as open up potential business opportunities to deploy such efficient robot agents within household, warehouse, retail, and diverse other industries.

Faculty Supervisor:

Liam Paull

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology

University:

Université de Montréal

Program: