Zhe Huang
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About me
I'm a 5th-year Ph.D. candidate advised by Prof. Katherine Driggs-Campbell at University of Illinois at Urbana-Champaign. My research interest is in Human-Robot Interaction and Artificial Intelligence. I do research on Learning-based Path Planning, Intention Tracking, Trajectory Prediction, Large Language Model Driven Robotics, and Integration of Prediction and Planning. Applications of my research include Collaborative Manufacturing, Autonomous Driving, and Social Navigation.
I received the B.Eng. degree in Energy and Power Engineering from Xi'an Jiaotong University in 2017, and received the M.S. degree in Mechanical Engineering from Stanford University in 2019.
News
[2024.04] We have released our main implementation for NIRRT* on the GitHub repo nirrt_star.
[2024.02] We have released our ROS implementation for NIRRT* on the GitHub repo PNGNav.
[2024.01] Our path planning paper NIRRT* is accepted by ICRA 2024.
[2023.01] Two papers Hierarchical Intetion Tracking and Intention Aware CrowdNav are accepted by ICRA 2023.
[2022.12] I finished my internship at Amazon Robotics as an Advanced Robotics Research Co-op!
[2022.12] I am excited to attend the 5th Robot Learning Workshop: Trustworthy Robotics at NeurIPS 2022 as an invited speaker!
[2022.08] I am excited to join Amazon Robotics as an Advanced Robotics Research Co-op to work on grasp learning research projects.
[2022.08] I finished my internship at Nuro as a PhD Intern!
[2022.08] We will present our work Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration on CASE 2022 Special Session on Adaptive and Resilient Cyber-Physical Manufacturing Networks.
[2022.05] I am excited to join Nuro as a PhD Intern to work on autonomous driving research projects.
[2022.05] Our work Insights from an Industrial Collaborative Assembly Project: Lessons in Research and Collaboration is selected for spotlight presentation at ICRA 2022 Workshop on Collaborative Robots and the Work of the Future.
[2022.04] I am honored to give a talk at Wuhan University titled “Human Behavior Modeling in Autonomous Driving and Collaborative Manufacturing” (自动驾驶与协同制造中的人类行为建模).
[2022.02] Our demo “Human-Robot Collaboration in Industrial Assembly Tasks” is awarded the Best Robotics Demo in Coordinated Science Laboratory Student Conference.
[2022.01] We will present GST on ICRA 2022.
[2021.12] We have released our code for GST on the GitHub repo gst.
[2021.12] One paper GST is accepted by RA-L.
[2021.06] We have released our code and pretrained models for MIF-WLSTM on the GitHub repo mifwlstm.
[2020.11] One paper MIF-WLSTM is accepted by RA-L.
[2020.05] One paper is accepted by ITSC 2020.
[2020.01] One paper is accepted by RA-L and ICRA 2020.
Publications
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Neural Informed RRT*: Learning-based Path Planning with Point Cloud State Representations under Admissible Ellipsoidal Constraints |
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Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks |
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Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph |
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Learning Sparse Interaction Graphs of Partially Detected Pedestrians for Trajectory Prediction |
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Long-Term Pedestrian Trajectory Prediction Using Mutable Intention Filter and Warp LSTM |
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Online Monitoring for Safe Pedestrian-Vehicle Interactions |
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3D Electromagnetic Reconfiguration Enabled by Soft Continuum Robots |
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A Voice Interface for Drilling Systems |
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High Accuracy Flight State Identification of a Self-Sensing Wing via Machine Learning Approaches |