Title: Learning by Robot manipulation demonstration via generative adverse networks
Approval Date:  Jan. 21


Research objectives:

  • Use of Generative adverse networks to generate control for manipulation (and demonstration) in the context of Humanoid robots.
  • Application: robots@home

Related roadmap thrusts and axis

– Thrust 2: New Algorithms for Energy-Efficient and Human Based AI

    • Axis 2.1: Cross learning between humans and machines

Project Members

Name Organisation Role
M. Mohamed-Kalil Jabri IMT Atlantique / The University of Adelaide PhD Student
A/Prof. Panagiotis Papadakis IMT Atlantique Primary PhD Advisor
Prof. Javen Shi The University of Adelaide Primary PhD Advisor
Dr. Ehsan Abbasnejad The University of Adelaide Secondary PhD Advisor

Project Funding 

  •  Brittany Region, The University of South Australia, SA

Start / Duration 

  •  Jan. 20 / 3 years