Multi-modal intention detection for robot repositioning based on physical human-robot interaction

The proposed project aims to look at different ways of combining touch and visual stimuli to enhance the awareness of a humanoid robot during interaction with humans. The goal is to have the robot capable of reacting to more complicated forms of touch. For example, allowing the robot to be physically repositioned through different combinations of human touch and visual cues, while maintaining certain criteria about body positioning. The expected outcome is a robot that is smarter and more reactive during physical human-robot interaction, and as a result safer to interact with.

Faculty Supervisor:

Wael Suleiman

Student:

Partner:

Université de Montpellier (CEFE, CNRS)

Discipline:

Engineering

Sector:

Technology; Manufacturing and Construction

University:

Université de Sherbrooke

Program:

Globalink Research Award

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