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Title: The Design, Education and Evolution of a Robotic Baby
Date: November 30, 2022 (Wednesday)
Time: 10:00 am - 12:00 pm EST
Location: Zoom (https://gatech.zoom.us/j/97318093429)
Hanqing Zhu
Ph.D. Candidate in Robotics
School of Aerospace Engineering
Georgia Institute of Technology
Committee:
Dr. Eric Feron (Advisor) - Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology
Dr. Kyriakos Vamvoudakis (Co-Advisor) - School of Aerospace Engineering, Georgia Institute of Technology
Dr. Dimitri Mavris - School of Aerospace Engineering, Georgia Institute of Technology
Dr. Jerome Hugues - Software Engineering Institute, Carnegie Mellon University
Dr. Emmanuel Roche - Clover.AI
Abstract:
Inspired by Alan Turing's idea of a child machine, I introduce the formal definition of a robotic baby, an integrated system with minimal world knowledge at birth, capable of learning incrementally and interactively, and adapting to the world. Within the definition, fundamental capabilities and system characteristics of the robotic baby are identified and presented as the system-level requirements. As a minimal viable prototype, the Baby architecture is proposed with a systems engineering design approach to satisfy the system-level requirements, which has been verified and validated with simulations and experiments on a robotic system. The capabilities of the robotic baby are demonstrated in natural language acquisition and semantic parsing in English and Chinese, as well as in natural language grounding, natural language reinforcement learning, natural language programming and system introspection for explainability. Furthermore, the education and evolution of the robotic baby are illustrated with real-world robotic demonstrations. Inspired by the genetic inheritance in human beings, knowledge inheritance in robotic babies and its benefits regarding evolution are discussed.
