Chen (Albert) Feng (冯宸)

I am a Ph.D. candidate in UAV Group, ECE at HKUST, supervised by Prof. Shaojie Shen. Prior to HKUST, I obtained a B.Eng from Harbin Institute of Technology and majored in Mechatronics Engineering (ME) in 2021.

I was a research intern from May. 2021 to Sept. 2021 in Video Group at Megvii Research of Megvii (Beijing, China). In my undergraduate study, I was an team member of computer vision group and mechanics group in Harbin Institute of Technology Competition Robotics Team (HITCRT) (Harbin, China).


Email / Google Scholar / Github / CV

News

  • 2024.06: Invited talk at TechBeat on the field of Aerial Coverage and Reconstruction.
  • 2024.05: A paper is selected as the finalist for ICRA 2024 Best UAV Paper Award.
  • 2024.02: A paper is accepted to RA-L.
  • 2024.01: Three papers are accepted to ICRA 2024.
  • 2023.12: I have passed Ph.D. Qualifying Examination to become a Ph.D. candidate.
  • 2023.08: Two papers are accepted to RA-L.
  • 2023.01: A paper is accepted to ICRA 2023.
  • 2022.06: A paper is accepted to CVPR 2022 Workshop.
  • Education
    PontTuset

    Ph.D. Candidate | Electronic and Computer Engineering (ECE), HKUST
    Time: 2021 - Present. Supervisor: Prof. Shaojie Shen

    PontTuset

    B.Eng | Mechatronics Engineering (ME), HIT
    Time: 2017 - 2021.

    Research

    My research focuses on robotics and deep learning, including perception, prediction, and planning. Before HKUST, my research worked on perception and trajectory prediction in autonomous driving. In the present stage, I focus on autonomous and intelligent aerial inspection/reconstruction/exploration/coverage, and 3D scene understanding.

    Publications

    (# for the corresponding author, * for equal contribution)
    PontTuset

    FALCON: Fast Autonomous Aerial Exploration using Coverage Path Guidance
    Yichen Zhang*, Xinyi Chen*, Chen Feng, Boyu Zhou#, and Shaojie Shen.
    [Under Review] Submitted to IEEE Transactions on Robotics (T-RO).

    This paper introduces FALCON, a novel Fast Autonomous expLoration framework using COverage path guidaNce, which aims at setting a new performance benchmark in the field of autonomous aerial exploration. FALCON effectively harnesses the full potential of online generated coverage paths in enhancing exploration efficiency.

    PontTuset

    FC-Hetero: Fast and Autonomous Aerial Reconstruction Using a LiDAR-Visual Heterogeneous Multi-UAV System
    Mingjie Zhang*, Chen Feng*, Zengzhi Li, Guiyong Zheng, Yiming Luo, Zhu Wang, Jinni Zhou, Shaojie Shen, and Boyu Zhou#.
    [Under Review] Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. Abu Dhabi, United Arab Emirates.
    Star

    We introduce FC-Hetero, a LiDAR-visual heterogeneous UAV Multi-UAV system that can support fast aerial coverage and reconstruction in complex environments.

    PontTuset

    OmniNxt: A Fully Open-source and Compact Aerial Robot with Omnidirectional Visual Perception
    Peize Liu, Chen Feng#, Yang Xu, Yan Ning, Hao Xu#, and Shaojie Shen.
    [Under Review] Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. Abu Dhabi, United Arab Emirates.
    Star

    We introduce OmniNxt, the first fully open-source aerial robotics platform with omnidirectional visual perception. OmniNxt boasts a compact size with exceptional computational resources. Thanks to our meticulous development, we endow OmniNxt with an expansive perception range and efficient resource consumption.

    PontTuset

    MASSTAR: A Multi-Modal Large-Scale Scene Dataset with a Versatile Toolchain for Surface Prediction and Completion
    Guiyong Zheng*, Jinqi Jiang*, Chen Feng*, Shaojie Shen, and Boyu Zhou#.
    [Under Review] Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. Abu Dhabi, United Arab Emirates.
    Star

    We propose MASSTAR, a Multi-modal lArge-scale Scene dataset with a verSatile Toolchain for surfAce pRediction and completion. We develop a versatile and efficient toolchain for processing the raw 3D data from the environments.

    PontTuset

    Star-Searcher: A Complete and Efficient Aerial System for Autonomous Target Search in Complex Unknown Environments
    Yiming Luo, Zixuan Zhuang, Neng Pan, Chen Feng, Shaojie Shen, Fei Gao, Hui Cheng, and Boyu Zhou#.
    IEEE Robotics and Automation Letters (RA-L), 2024. Presented at IROS 2024, Abu Dhabi, United Arab Emirates.
    Star

    We propose Star-Searcher, a complete and efficient aerial system for autonomous target search in complex unknown environments. Our aerial system incorporates specialized sensor suites, mapping, and planning modules, all geared towards improving task efficiency and completeness.

    PontTuset

    FC-Planner: A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes
    Chen Feng, Haojia Li, Mingjie Zhang, Xinyi Chen, Boyu Zhou#, and Shaojie Shen.
    IEEE International Conference on Robotics and Automation (ICRA), 2024. Yokohama, Japan. (Best UAV Paper Award Finalist)
    Star Talk

    We propose FC-Planner, a skeleton-guided planning framework tailored for fast coverage of large and complex 3D scenes, which results in the generation of high-quality coverage paths and high computational efficiency.

    PontTuset

    MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Prediction
    Chen Feng, Hangning Zhou, Huadong Lin, Zhigang Zhang, Ziyao Xu, Chi Zhang, Boyu Zhou#, and Shaojie Shen.
    IEEE Robotics and Automation Letters (RA-L), 2023. Presented at ICRA 2024, Yokohama, Japan.

    We propose MacFormer, an one-stage Map-Agent Coupled Transformer for real-time and robust trajectory prediction that explicitly incorporates map constraints into the network achieving state-of-the-art performance with significantly lower inference latency and fewer parameters.

    PontTuset

    AutoTrans: A Complete Planning and Control Framework for Autonomous UAV Paylaod Transportation
    Haojia Li, Haokun Wang, Chen Feng, Fei Gao#, Boyu Zhou#, and Shaojie Shen.
    IEEE Robotics and Automation Letters (RA-L), 2023. Presented at ICRA 2024, Yokohama, Japan.
    Star

    We propose AutoTrans, a systematic solution for fully autonomous aerial payload transportation that includes a real-time planning solution to generate smooth trajectories and an adaptive NMPC with a hierarchical disturbance compensation strategy to overcome unknown external perturbations as well as inaccurate model parameters.

    PontTuset

    PredRecon: A Prediction-boosted Planning Framework for Fast and High-quality Autonomous Aerial Reconstruction
    Chen Feng, Haojia Li, Fei Gao, Boyu Zhou#, and Shaojie Shen.
    IEEE International Conference on Robotics and Automation (ICRA), 2023. London, UK.
    Star

    We propose PredRecon, a prediction-boosted planning framework that can efficiently reconstruct high-quality 3D models for the target areas in unknown environments with a single flight.

    PontTuset

    TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction
    Yuting Wang*, Hangning Zhou*,#, Zhigang Zhang*, Chen Feng, Huadong Lin, Chaofei Gao, Yizhi Tang, Zhenting Zhao, Shiyu Zhang, Jie Guo, Xuefeng Wang, Ziyao Xu, and Chi Zhang.
    IEEE / CVF Computer Vision and Pattern Recognition Conference Workshop on Autonomous Driving (CVPRW), 2022. New Orleans, USA.

    We propose TENET to enhance the trajectory temporal encoding via Temporal Flow Header. Besides, an efficient K-means ensemble method is used. Using our Transformer network and ensemble method, we win the first place of Argoverse 2 Motion Forecasting Challenge with the state-of-the-art brier-minFDE score of 1.90.

    Honors & Awards

    2024.05, ICRA 2024 Best UAV Paper Award Finalist - IEEE.

    2021.09, Postgraduate Studentship - HKUST.

    2021.06, Outstanding Graduate - HIT.

    2020.08, ABU ROBOCON Robotics Competition First Prize - ABU.

    2019.08, National University Students Robotics Competition, RoboMaster First Prize - DJI.

    2018.12, Outstanding Student - HIT.

    2018.12, National Scholarship - Ministry of Education, PRC.

    Talks

    2024.06, Fast and Autonomous Aerial Coverage and Reconstruction of Large-scale Scenes - TechBeat .

    Service

    Reviewer: RA-L, ICRA, IROS, CVPR

    Teaching Assistant:

  • ELEC1100 Introduction to Electro-Robot Design (2023 Fall)
  • ELEC5660 Introduction to Aerial Robots (2024 Spring)
  • About Me

    Skills: Python / C++ / Matlab, PyTorch / MegEngine, Linux, ROS, OpenCV, SolidWorks, Adams, ANSYS, Mechanical design


    Last update: 2024.06.18. Thanks.