About Me

My name is Xiaodi Yuan (袁小迪), and I also go by Ada.

I am a first-year PhD student at UC San Diego, advised by Prof. Hao Su. I received my B.Eng. degree from IIIS ("Yao Class"), Tsinghua University, where I worked with Prof. Li Yi on 3D shape reconstruction, and Prof. Tao Du on physics-based simulation.

My research interests are computer graphics and physics-based simulation. I am working on building fast and realistic simulation environments for embodied AI.


Publications [More]

General-Purpose Sim2Real Protocol for Learning Contact-Rich Manipulation With Marker-Based Visuotactile Sensors

Weihang Chen, Jing Xu, Fanbo Xiang, Xiaodi Yuan, Hao Su, Rui Chen

TRO 2024 [PDF]

We build a general-purpose Sim2Real protocol for manipulation policy learning with marker-based visuotactile sensors. To improve the simulation fidelity, we employ an FEM-based physics simulator that can simulate the sensor deformation accurately and stably for arbitrary geometries. We further propose a novel tactile feature extraction network that directly processes the set of pixel coordinates of tactile sensor markers and a self-supervised pre-training strategy to improve the efficiency and generalizability of RL policies.

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

Jiayuan Gu, Fanbo Xiang, Xuanlin Li, Zhan Ling, Xiqiang Liu, Tongzhou Mu, Yihe Tang, Stone Tao, Xinyue Wei, Yunchao Yao, Xiaodi Yuan, Pengwei Xie, Zhiao Huang, Rui Chen, Hao Su

ICLR 2023 [PDF] [Project] [Code]

A unified benchmark for learning generalizable robotic manipulation skills powered by SAPIEN.


Projects [More]

SAPIEN SPH: A Simple GPU-based Implementation of PCISPH

[Code]

Homework project for the course “Physical Simulation” at UCSD instructed by Prof. Albert Chern.

ManiSkill-ViTac: Vision-based-Tactile Manipulation Skill Learning Challenge 2024

ICRA 2024 Workshop [Project]

The ManiSkill-ViTac Challenge aims to provide a standardized benchmarking platform for evaluating the performance of vision-based-tactile manipulation skill learning in real-world robot applications. The challenge is supported by the GPU-based IPC simulator I developed.