Max Yang

Max Yang

PhD Student in Robotics and AI

University of Bristol

Biography

I am a PhD student at the University of Bristol and Bristol Robotics Laboratory, under the supervision of Prof. David Barton and Prof. Nathan Lepora. My current research is on sim-to-real deep reinforcement learning and tactile perception for robot manipulation. My interests lie in machine learning methods for robot perception and control.

Before that, I obtained my MEng degree in Aeronautical Engineering at Imperial College London where I worked in control theory and optimal control.

I’m currently seeking PhD internships for Fall/Winter 2024.

Interests
  • Tactile Sensing
  • Dexterous Manipulation
  • Sim-to-Real Deep Reinforcement Learning
Education

  • PhD in Engineering Mathemtics, 2025

    University of Bristol

  • MEng in Aeronautical Engineering, 2019

    Imperial College London

Recent Publications

AnyRotate: Gravity Invariant In-Hand Object Rotation with Sim-to-Real Touch
Max Yang, Chenghua Lu, Alex Church, Yijiong Lin, Chris Ford, Efi Psomopoulou, David A.W. Barton, Nathan F. Lepora, Conference of Robot Learning (CoRL) 2024
PDF Cite Video Website
AnyRotate: Gravity Invariant In-Hand Object Rotation with Sim-to-Real Touch
Snap-it, Tap-it, Splat-it: Tactile-Informed 3D Gaussian Splatting for Reconstructing Challenging Surfaces
Mauro Comi, Allessio Tonioni, Max Yang, Jonathan Tremblay, Valts Blukis, Yijiong Lin, Nathan F. Lepora, Laurence Aitchison, Under Review 2024
PDF Cite
Snap-it, Tap-it, Splat-it: Tactile-Informed 3D Gaussian Splatting for Reconstructing Challenging Surfaces
Bi-Touch: Bimanual Tactile Manipulation with Sim-to-Real Deep Reinforcement Learning
Yijiong Lin, Alex Church, Max Yang, Haoran Li, John Lloyd, Dandan Zhang, Nathan F. Lepora, Robotics and Automation Letters (RA-L) 2023
PDF Cite Code Website
Bi-Touch: Bimanual Tactile Manipulation with Sim-to-Real Deep Reinforcement Learning
Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing
Max Yang, Yijiong Lin, Alex Church, John Lloyd, Dandan Zhang, David A.W.Barton, Nathan F. Lepora, Robotics and Automation Letters (RA-L) 2023
PDF Cite Code Video Website
Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing
Tac-VGNN: A Voronoi Graph Neural Network for Pose-Based Tactile Servoing
Wen Fan, Max Yang, Yifan Xing, Nathan F. Lepora, Dandan Zhang, International Conference on Robotics and Automation (ICRA) 2023
PDF Cite Code Video Website
Tac-VGNN: A Voronoi Graph Neural Network for Pose-Based Tactile Servoing

Experience

 
 
 
 
 
PhD in Engineering Mathematics
University of Bristol
October 2021 – Present Bristol, United Kingdom
 
 
 
 
 
Research and Development Engineer
Sagentia Innovation
September 2019 – September 2021 Cambridge, United Kingdom
 
 
 
 
 
MEng in Aeronautical Engineering
Imperial College London
October 2015 – June 2019 London, United Kingdom
 
 
 
 
 
Research and Technology Intern
Airbus Commercial Aircraft
June 2018 – September 2018 Toulous, France

Projects

Visuo-Tactile Pick and Place
We present a visuo-tactile robotic system for precise food handling for the Robosoft 2023 Manipulation Competition. Our system is able to handle complex shelf configurations, with tasks including bin-picking and drink pouring.
PDF Website
Visuo-Tactile Pick and Place
Reinforcement Learning from Scratch
An example repository containing various reinforcement learning algorithms applied to OpenAI gym environemnts.
Code
Reinforcement Learning from Scratch
Optimal Control for Cancer Treatment
We developed an optimal control algorithm that combines genetic algorithms and lyapunov stability theory to obtain an optimal delivery strategy of chemotherapy during the treatment of cancer.
PDF Code
Optimal Control for Cancer Treatment

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