Open Thesis

Diffusion Model-based Imitation Learning for Robot Manipulation Task


Diffusion models are powerful generative models that enable many successful applications, such as image, video, and 3D generation from texts. It's inspired by non-equilibrium thermodynamics, which defines a Markov chain of diffusion steps to slowly add random noise to data and then learn to reverse the diffusion process to construct desired data samples from the noise. 

In this work, we aim to explore the application of the diffusion model or its variants in imitation learning and evaluate it on the real-world Franka robot arm.


  • Good Programming Skills (Python, C++)
  • Knowledge about Ubuntu/Linux/ROS
  • Motivation to learn and conduct research


(Please attach your CV and transcript)


Dong Yang

Ongoing Thesis

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