[VR 2020] Extracting and transferring hierarchical knowledge to robots using virtual reality


We study the knowledge transfer problem by training the task of folding clothes in the virtual world using an Oculus Headset and validating with a physical Baxter robot. We argue such complex transfer is realizable if an abstract graph-based knowledge representation is adopted to facilitate the process. An And-Or-Graph (AOG) grammar model is introduced to represent the knowledge, which can be learned from the human demonstrations performed in the Virtual Reality (VR), followed by the case analysis of folding clothes represented and learned by the AOG grammar model.

In 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
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Zhenliang Zhang
Zhenliang Zhang
Research Scientist of AI

My research interests include wearable computing, machine learning, Cognitive Reasoning, and mixed/virtual reality.