Research Interests
Robotics - Science: I'm interested in learning and planning for multi-robot and human-robot systems.
Robotics - Systems: I'm interested in developing robotic systems for real-world problems.
Demos
I developed this learning from YouTube videos system and presented it [here].
I contributed to the development of a robot hair brushing demo and presented the demo in NeurIPS 2019!
I developed this fun feeding demo for Thanksgiving 2019!
Presentations
- A MIP-based Approach for Multi-Robot Geometric Task-and-Motion Planning, IEEE International Conference on Automation Science and Engineering, August 2022. [slides]
- Robot Learning Collaborative Manipulation Plans from YouTube Cooking Videos, R:SS Workshop on Emergent Behaviors in Human Robot Systems, July 2020. [slides]
[video]
- Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills, Southern California Robotics Symposium, April 27 2019. [slides] [poster]
Publications
Journal Papers
- Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman. Scaling Simulation-to-Real Transfer by Learning a Latent Space of Robot Skills.
International Journal of Robotics Research (IJRR), 2020. [paper]
- Chaoyang Zhu, Kejie Huang, Shuyuan Yang, Ziqi Zhu, Hejia Zhang, Haibin Shen. An Efficient Hardware Accelerator for Structured Sparse
Convolutional Neural Networks on FPGA. IEEE Transactions on Very Large Scale Integration Systems (TVLSI), 2020. [paper]
Conference Proceedings
- Shivin Dass*, Karl Pertsch*, Hejia Zhang, Youngwoon Lee, Joseph J. Lim, Stefanos Nikolaidis. Assisted Teleoperation for Scalable Robot Data Collection. In Robotics: Science and Systems (R:SS), 2023. [arXiv] [project page] [code]
- Hejia Zhang, Shao-Hung Chan, Jie Zhong, Jiaoyang Li, Sven Koenig, Stefanos Nikolaidis. A MIP-Based Approach for Multi-Robot Geometric Task-and-Motion Planning.
In The 18th IEEE International Conference on Automation Science and Engineering (CASE), 2022. [pdf]
- Hejia Zhang*, Matthew Fontaine*, Amy Hoover, Julian Togelius, Bistra Dilkina, Stefanos Nikolaidis. Video Game Level Repair via Mixed Integer Linear Programming.
In The 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-20), 2020 (Oral Presentation; 25% acceptance rate). [pdf] [paper] [bibtex] [code]
- Hejia Zhang, Po-Jen Lai, Sayan Paul, Suraj Kothawade and Stefanos Nikolaidis. Learning Collaborative Action Plans from Unlabeled YouTube Videos. International
Symposium on Robotics Research (ISRR), 2019. [pdf] [bibtex]
- Ryan Julian*, Eric Heiden*, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman.
Scaling simulation-to-real transfer by learning composable robot skills. In International Symposium on Experimental Robotics (ISER), 2018. [pdf] [bibtex]
Workshop Papers and Abstracts
- Shivin Dass, Karl Pertsch, Hejia Zhang, Youngwoon Lee, Joseph J. Lim, Stefanos Nikolaidis. Assisted Teleoperation for Scalable Robot Data Collection.
In Conference on Robot Learning (CoRL) Workshop on Pre-training Robot Learning, 2022.
- Hejia Zhang, Shao-Hung Chan, Jie Zhong, Jiaoyang Li, Sven Koenig, Stefanos Nikolaidis. A MIP-Based Approach for Multi-Robot Geometric Task-and-Motion Planning.
In Southern California Robotics Symposium (SCR), 2022. [pdf] [bibtex]
- Hejia Zhang, Stefanos Nikolaidis. Robot Learning Collaborative Manipulation Plans from YouTube Cooking Videos. In R:SS Workshop on Emergent Behaviors in Human-Robot Systems, 2020. [pdf]
[bibtex] [talk] [slides]
- Hejia Zhang, Eric Heiden, Stefanos Nikolaidis, Joseph J. Lim, Gaurav S. Sukhatme. Auto-conditioned Recurrent Mixture Density Networks for Learning
Generalizable Robotic Manipulation Skills. In Southern California Robotics Symposium (SCR), 2019. [pdf] [bibtex]
- Zhanpeng He*, Ryan Julian*, Eric Heiden, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman. Simulator Predictive Control: Using Learned Task
Representations and MPC for Zero-Shot Generalization and Sequencing. In Conference
on Neural Information Processing Systems (NeurIPS) 2018 Deep Reinforcement Learning Workshop. [pdf] [video] [bibtex]
Technical Reports
- Hejia Zhang, Jie Zhong, Stefanos Nikolaidis. Zero-Shot Imitating Collaborative Manipulation Plans from YouTube Cooking Videos. In arXiv [arXiv]
- Eric Heiden*, David Millard*, Hejia Zhang and Gaurav S. Sukhatme. Interactive Differentiable Simulation. In arXiv. [arXiv]
[bibtex]
- Hejia Zhang, Eric Heiden, Stefanos Nikolaidis, Joseph J. Lim and Gaurav S. Sukhatme. Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills.
In arXiv. [pdf] [video] [poster] [arXiv] [bibtex]