Mapping High-Level Workflows to Low-Level Robotic Actions

We are developing a robotic platform and agent that is able to translate instructions (e.g. “bring me the newspaper”) into a series of low-level programs (moving between rooms, locating objects, interacting with objects) and executing these autonomously. Traditionally, in hierarchical reinforcement learning, tasks are executed sequentially, but we would like to focus on parallelization and parameterization of low-level skills.

Faculty Supervisor:

Liam Paull

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology

University:

Université de Montréal

Program:

Accelerate

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