I’m a researcher at Meta Fundamental AI Research (FAIR) in Menlo Park, focusing on Embodied AI and Robotics Manipulation.
I earned my Ph.D. from UC Berkeley in Dec 2023, under the guidance of Prof. Masayoshi Tomizuka. Additionally, I had the opportunity to contribute to the Google’s Everyday Robots project in summer 2020 and 2022.
Outside of work, I am a marathon runner.
News
- 02/2025: We released the paper: Dexterity Gen: Foundation Controller for Unprecedented Dexterity
- 07/2024: Paper: Generalizable whole-body global manipulation of deformable linear objects by dual-arm robot in 3-D constrained environments accepted by International Journal of Robotics Research (IJRR).
- 01/2024: Paper: Distributed Multi-agent Interaction Generation with Imagined Potential Games accepted by American Control Conference (ACC) 2024.
- 01/2024: I started as a Research Engineer in the Embodied AI team at Meta FAIR.
- 12/2023: I successfully defended my Ph.D. dissertation and obtained the Ph.D. degree. Here is my thesis.
- 12/2023: Paper: Robot manipulation task learning by leveraging se (3) group invariance and equivariance accpeted by IEEE Robotics and Automation Letters (RA-L).
- 09/2023: Paper: Efficient Sim-to-real Transfer of Contact-Rich Manipulation Skills with Online Admittance Residual Learning (website) accepted by CoRL 2023.
- 06/2023: Paper: A coarse-to-fine framework for dual-arm manipulation of deformable linear objects with whole-body obstacle avoidance (video) won the Best Paper Award at the ICRA 2023 Workshop on Representing and Manipulating Deformable Objects.
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- 01/2023: Paper: A coarse-to-fine framework for dual-arm manipulation of deformable linear objects with whole-body obstacle avoidance accepted by ICRA 2023.
- 01/2023: Paper: Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning accepted by ICRA 2023.
- 05/2022: I begin my Resident at (Google) X, the Moonshot Factory on the Everyday Robots project.
- 05/2022: Paper: Safe Online Gain Optimization for Cartesian Space Variable Impedance Control accepted by CASE 2022
- 02/2022 Paper: Offline-Online Learning of Deformation Model for Cable Manipulation With Graph Neural Networks accepted by IEEE Robotics and Automation Letters (RA-L).
- 02/2022: Paper: Robotic cable routing with spatial representation accepted by IEEE Robotics and Automation Letters (RA-L).
- 01/2022: Paper: Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Tasks accepted by ICRA 2022
- 01/2022: Paper: BPOMP: A Bilevel Path Optimization Formulation for Motion Planning accepted by ACC 2022
- 06/2021: Paper: Trajectory Splitting: A Distributed Formulation for Collision Avoiding Trajectory Optimization accepted by IROS 2021.
- 06/2021: Paper: Online Learning of Unknown Dynamics for Model-Based Controllers in Legged Locomotion accepted by IEEE Robotics and Automation Letters (RA-L).
- 01/2021: Paper: Contact Pose Identification for Peg-in-hole Assembly under Uncertainties accepted by ACC 2020.
- 05/2020: I begin my robotics research intern at (Google) X, the Moonshot Factory.
- 06/2019: Paper: Robust Deformation Model Approximation for Robotic Cable Manipulation accepted by IROS 2019.
- 07/2019: I begin my robotics reserach intern at FANUC Advanced Reserach Laboratory.
- 07/2018: Paper: A Framework for Manipulating Deformable Linear Objects by Coherent Point Drift accepted by IEEE Robotics and Automation Letters (RA-L).
Research
Dexterity Gen: Foundation Controller for Unprecedented Dexterity
Zhao-Heng Yin, Changhao Wang, Luis Pineda, Francois Hogan, Krishna Bodduluri, Akash Sharma, Patrick Lancaster, Ishita Prasad, Mrinal Kalakrishnan, Jitendra Malik, Mike Lambeta, Tingfan Wu, Pieter Abbeel, and Mustafa Mukadam
Technical Report
A coarse-to-fine framework for dual-arm manipulation of deformable linear objects with whole-body obstacle avoidance
Mingrui Yu, Kangchen Lv, Changhao Wang, Masayoshi Tomizuka, Xiang Li
ICRA 2023
⭐ Best Workshop Paper Award ⭐
[Paper] [Website] [Presentation]
Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning
Zheng Wu, Yichen Xie, Wenzhao Lian, Changhao Wang, Yanjiang Guo, Jianyu Chen, Stefan Schaal, Masayoshi Tomizuka
ICRA 2023
[Paper]
Prim-LAfD: A Framework to Learn and Adapt Primitive-Based Skills from Demonstrations for Insertion Tasks
Zheng Wu, Wenzhao Lian, Changhao Wang, Mengxi Li, Stefan Schaal, Masayoshi Tomizuka
IFAC 2023
[Paper]
Trajectory splitting: A distributed formulation for collision avoiding trajectory optimization
Changhao Wang, Jeffrey Bingham, Masayoshi Tomizuka
IROS 2021
[Paper]
Contact pose identification for peg-in-hole assembly under uncertainties
Shiyu Jin, Xinghao Zhu, Changhao Wang, Masayoshi Tomizuka
American Control Conference (ACC) 2021
[Paper]
A framework for manipulating deformable linear objects by coherent point drift
Te Tang*, Changhao Wang*, Masayoshi Tomizuka
IEEE Robotics and Automation Letters (RA-L) 2018
[Paper]