Imitation learning based control for quadrupedal robots

This project aims to make quadruped robots smarter and more versatile by adding a 360-degree camera and a robot arm into a reinforcement learning control system. The quadruped robots will undergo training with these upgrades in a simulation environment before being deployed in real-world scenarios. These upgrades will help the robots better understand their surroundings and interact with objects, making them more useful in real-world situations like search and rescue missions or exploring rough terrain. By working on this project, participating institutions will gain valuable insights into advanced robotics technology, which can be applied to various fields such as healthcare, manufacturing, and disaster response, ultimately advancing scientific knowledge and societal well-being.

Faculty Supervisor:

Wael Suleiman

Student:

Partner:

National Institute of Advanced Industrial Science and Technology

Discipline:

Engineering

Sector:

Education; Professional, scientific and technical services

University:

Université de Sherbrooke

Program: