Email: zhanteng (at) hku (dot) hk
The University of Hong Kong, HK : Nov. 2025 - Present
Postdoctoral Fellow
Centre for Transformative Garment Production, HK : Jun. 2025 - Oct. 2025
Postdoctoral Fellow
Temple University, US : Aug. 2019 - Aug. 2024
Research/Teaching Assistant
Southern University of Science and Technology, CN : Jun. 2018 - Jul. 2019
Research Assistant
Temple University, US : Aug. 2019 - Aug. 2024
Doctor of Philosophy in Mechanical Engineering (GPA=4.0)
Dissertation title: Robot Navigation in Crowded Dynamic Scenes
Harbin Institute of Technology, CN : Sept. 2015 - Jan. 2018
Master of Engineering in Information and Communication Engineering
Zhengzhou University, CN : Sept. 2011 - Jul. 2015
Bachelor of Engineering in Electronic Information Engineering
- Supervised by Prof. Philip Dames Sept. 2019 - Present
Environment Perception & Scene Understanding (Semantic2D): Addressed the critical gap in 2D lidar semantics by proposing Semantic2D (the first 2D lidar semantic segmentation dataset), the SALSA semi-automatic labeling framework, and S3-Net, a hardware-friendly stochastic segmentation algorithm.
Stochastic Environment Prediction (SCOPE): Proposed a family of software-optimized Stochastic Cartographic Occupancy Prediction (SCOPE) engines. Successfully modeled the complex dynamics of robots, moving objects, and static scenes while providing real-time uncertainty estimation for downstream navigation tasks.
Uncertainty-Aware Navigation Framework (SCOPE-PU): Pioneered a hardware-friendly predictive navigation architecture by incorporating the SCOPE prediction engine with both model-based and learning-based control policies. Demonstrated superior safety margins in both high-fidelity simulations and physical robotic experiments.
Crowded Environment Representation for Navigation: Proposed novel preprocessed environment representations tailored to crowded dynamic spaces, enabling concise and transferable abstractions of environmental states. Demonstrated strong generalization to unseen environments through evaluation with an imitation learning-based policy.
Crowd-Aware DRL Control Policy (DRL-VO): Designed a deep reinforcement learning-based control policy driven by a novel velocity obstacle-based reward function, achieving an optimal balance between safety and navigation efficiency in highly dynamic environments.
Human-Robot Interaction Studies for Social Navigation: Organized and conducted interdisciplinary human-robot studies for socially-aware robot navigation in collaboration with psychology researchers. Contributed to experimental design, study execution, and behavioral analysis to evaluate human comfort and social acceptance during robot navigation.
Simulation Infrastructure: Built a highly realistic 3D human-robot interaction Gazebo simulator, serving as a robust testbed for training and evaluating neural network-based navigation policies.
Github repositories:
[3D human-robot interaction Gazebo simulator], [Semantic2D], [Stochastic occupancy grid map predictor], [Crowd-aware control policy], [Uncertainty-aware control framework] .
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- Supervised by Prof. Philip Dames Jun. 2020 - Mar. 2021
Task-Specific Visual Perception Integration: Engineered a fine-tuned YOLOv3 detection pipeline utilizing custom-collected and annotated datasets for tiny object tracking (e.g., water bottles), successfully deployed on real-world robotic fleets.
Sensor Modeling for Probabilistic Filters: Proposed and validated a novel experimental characterization method for range-bearing sensor models (observation, detection, and clutter) within Probability Hypothesis Density (PHD) filters.
Github repositories:
[Bottle detector], [Sensor models].
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- Supervised by Prof. Philip Dames Sept. 2020 - Oct. 2021
Industrial System Integration & Control: Architected an intermediate management system linking high-level ROS embedded controllers (with stereo vision) to low-level Roboteq drive controllers, enabling autonomous material handling for industrial ground vehicles (ASI FRED2500).
Digital Twin for Factory Scenarios: Developed a comprehensive 3D Gazebo simulator for industrial ground vehicles navigating magnetic tape roadways, streamlining the sim-to-real deployment pipeline.
Github repositories:
Doctoral Dissertation:
Zhanteng Xie. “Robot Navigation in Crowded Dynamic Scenes.” Temple University. 2024.
Peer-Reviewed Journal Publications:
Pujie Xin, Zhanteng Xie, and Philip Dames. “Towards Predicting Collective Performance in Multi-Robot Teams.” IEEE Transactions on Robotics (T-RO), 41, 5229 - 5245, 2025. [arXiv]
Zhanteng Xie and Philip Dames. “SCOPE: Stochastic Cartographic Occupancy Prediction Engine for Uncertainty-Aware Dynamic Navigation.” IEEE Transactions on Robotics (T-RO), 41, 4139 - 4158, 2025. [arXiv], [video], [Github(predictor)], [Github(navigation)]
Zhanteng Xie and Philip Dames. “DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles.” IEEE Transactions on Robotics (T-RO), 39(4), 2700-2719, 2023. [arXiv], [video], [Github]
Xuesu Xiao, Zifan Xu, Zizhao Wang, Yunlong Song, Garrett Warnell, Peter Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, and Philip Dames. "Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Benchmark Autonomous Robot Navigation Challenge at ICRA 2022 [Competitions]." IEEE Robotics & Automation Magazine (RAM), 29(4), 148-156, 2022. [Github]
Jun Chen, Zhanteng Xie, and Philip Dames. “The Semantic PHD Filter for Multi-class Target Tracking: From Theory to Practice.” Robotics and Autonomous Systems (RAS), 149, 2022. [Github]
Peer-Reviewed Conference Publications:
Lindsay Ouellette, Julia Zortea, Alexandra Capalbo, Raz Shermister, Charles Furtado, Donald Hantula, Philip Dames, and Zhanteng Xie. “Too close for comfort? Navigating personal space in human-robot encounters.” Northeast Business & Economics Association (NBEA) Conference. 2024.
Zhanteng Xie and Philip Dames. “Stochastic Occupancy Grid Map Prediction in Dynamic Scenes.” Conference on Robot Learning (CoRL), 2023. [arXiv], [Github]
Zhanteng Xie, Pujie Xin, and Philip Dames. “Towards Safe Navigation Through Crowded Dynamic Environments.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
Publications Under Review:
Zhanteng Xie, Yipeng Pan, Yinqiang Zhang, Jia Pan, and Philip Dames. “Semantic2D: Enabling Semantic Scene Understanding with 2D Lidar Alone.” arXiv preprint arXiv:2409.09899, 2026. [arXiv], [video], [Dataset], [Github]
Yinqiang Zhang, Liang Lu, Yipeng Pan, Maolin Lei, Yuhan Xie, Zhanteng Xie, Xiaowei Luo, and Jia Pan, BIM-Loc: BIM-Integrated Discrepancy-Aware LiDAR-based Indoor Localization, 2026. [website]
Lindsay Ouellette, Julia Zortea, Alexandra Capalbo, Raz Shermister, Philip Dames, Zhanteng Xie, Charles Furtado, and Donald Hantula. “Too close for comfort? Navigating personal space in human-robot encounters.”
Lindsay Ouellette, Drew Kronstadt, Sunvy Yalamarthy, Philip Dames, Zhanteng Xie, Slobodan Vucetic, and Donald Hantula. “Human vs. Robot Approaches: The Influence of Negative Attitudes on Comfort Levels.”
Champion (1st Place), The ICRA Arena Challenge (Social Navigation). IEEE International Conference on Robotics and Automation (ICRA), 2025.
3rd Place (1st in Simulation Portion), Benchmark Autonomous Robot Navigation (BARN) Challenge. IEEE International Conference on Robotics and Automation (ICRA), 2022.
First-Class Postgraduate Academic Scholarship, Harbin Institute of Technology, 2016.
National 2nd Prize & Provincial 1st Prize, National Undergraduate Electronic Design Contest (NUEDC), China, 2013.
Multiple Academic Scholarships & Programming Awards, Zhengzhou University (including 3rd Place in University ACM Programming Contest and Excellent Student Scholarships), 2012--2014.
Professional Reviewing:
IEEE Transactions on Robotics (T-RO), 2023 - Present
IEEE/ASME Transactions on Mechatronics (TMECH), 2025 - Present
Robotics and Autonomous Systems (RAS), 2024 - Present
IEEE Robotics and Automation Letters (RA-L), 2021 - Present
IEEE International Conference on Robotics and Automation (ICRA), 2021 - Present
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 - Present
Teaching Service:
Course Co-designer and Co-instructor, MEE4411/5411: Introduction to Mobile Robotics, Spring 2024. Designed weekly project assignments and led group-based hardware experiments for the Learning-Based Control module (4 weeks).
Teaching Assistant, mechanical engineering courses, 2022--2023. Responsible for assignment grading and office-hour support for Engineering Dynamics, Advanced Thermodynamics and Combustion, and Heat and Mass Transfer.
Programming & Scripting: Python, C/C++, MATLAB, Bash/Shell, Verilog.
Robotics & Simulation Infrastructure: ROS1/ROS2, NVIDIA Isaac Sim, Gazebo, Habitat, Flatland, PedSim.
Machine Learning & AI Frameworks: PyTorch, PyTorch Geometric, TensorFlow, Stable-Baselines3 (DRL), Caffe, NCNN, NNIE, LLM/API Deployment (LiteLLM, Cloudflare Workers).
Robotic Platforms: Human-scale Wheeled-Bipedal (TRON1), UGVs (TurtleBot2/3, Clearpath Jackal, ASI Fred AGV), Manipulators (AIRBOT Play).
Embedded Computing & Edge AI: NVIDIA Jetson Series (Orin/Xavier/TX2), Raspberry Pi, ARM-based Microcontrollers (STM32), FPGA (Altera/Xilinx series with Vivado/Quartus).
Hardware & Sensor Integration: 3D/2D lidar (Hokuyo, Slamtec, VanJee), Stereo/RGB-D Vision (Intel RealSense series, ZED), PCB \& Electronic Circuit Design (Altium Designer, Multisim).
- Supervised by Prof. Hao YU Jun. 2018 - Jul. 2019
Goal - to realize the video image real-time processing in embedded platforms without GPUs, including video detection and video analysis;
Tasks -
1. To realize the real-time object detection in video using SSD/YOLO network combined with MobileNet in mobile platforms, including training full-precision network using Caffe architecture, writing related inference code using NCNN architecture and NNIE architecture, and getting 8bits quantized network using DoReFa algorithm.
2. To realize the real-time video analysis using RNN combined with tensor compression in mobile platforms.
Outcome – realized the video object detection demo on RK3399, HiKey970, and Hi3559A platforms, achieving 10 FPS processing speed on HiKey970 (full-precision network) and 18 FPS processing speed on Hi3559A (8bits quantized network).
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Apr. 2016-Jun. 2017
Goal - to devise and realize the WCDMA communication system for LEO Satellites;
Tasks -
1. To realize the QPSK system via M-Language of MATLAB, and verify the BER performance of the QPSK system under the AWGN channel, Rayleigh channel, and Rice channel;
2. To set up the downlink of the WCDMA communication simulation system for LEO satellites based on the Simulink platform, which includes the realization of physical layer algorithms, and verify the system’s BER performance under the environment of low SNR and large Doppler shift;
3. To do hardware implementation of the downlink of the WCDMA communication system for LEO satellites via Verilog language based on Xilinx FPGA platforms, which includes spreading spectrum, scrambling, shaping filter, up/down-conversion, code synchronization, carrier synchronization, and AWGN channel simulator, and complete the measurement of system’s BER performance;
4. To participate in the uplink design of the WCDMA communication system for LEO satellites, including parameter designs such as physical channel rate, bandwidth and IF frequency, and the physical layer architecture design;
5. To research the CDMA uplink power control algorithms for LEO satellites, and try to use the Game theory to solve the power control problem;
Outcome - established the simulation demo system and the hardware demo system for the communication system of LEO satellites.
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- Supervised by Prof. Fei WANG Oct. 2015-Nov. 2015
Goal - to realize Faddeev’s algorithm which is use for matrix computations by using systolic arrays based on FPGA;
Tasks -
1. To realize 3x3 matrix floating point multiplication by using basic systolic arrays in Verilog language and do related simulation verifications including the conversion of data format between floating point numbers and real numbers by using testbench and Modelsim software;
2. To implement ordinary mode systolic arrays and dual mode systolic arrays for Faddeev’s algorithm via Verilog language based on Xilinx FPGA platforms and compare the resource consumption and performance between these two different systolic architectures.
Outcome – implemented 4x4 matrix floating point computations by using ordinary mode systolic arrays and dual mode systolic arrays separately.
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- Supervised by Prof. JianWei JI Oct. 2014-Mar. 2015
Goal - to generate the sinusoidal wave, square wave, and triangular wave, and set tunable square wave frequency in the range of 0-1MHz and the tunable voltage of 0-5V;
Tasks -
1. To apply C Language to edit the bottom-driver code (namely 12864 LCD driver, AD9834 driver, matrix keyboard driver, and code switch driver), manipulation function code, and multi-layer interactive menu code by using STC12-SCM;
2. To design the digital signal source panel, including its size, silk screen, and the layout of LCDs, buttons, and switches;
3. To join in circuit board welding, hardware debugging, and signal source components assembly for more than 100 sets of digital signal source generators;
Outcome - designed more than 100 sets of digital signal source generators for certain district areas.
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- Supervised by Prof. JiaYou SONG Apr. 2014-Jul. 2014
Goal - to sense weather and control the window automatically; to conduct real-time monitoring of environmental quality; to realize the function of remote control;
Tasks -
1. To complete the circuit principle design and place & route of PCB circuit board via Altium Designer software;
2. To prepare circuit boards and conduct hardware debugging;
3. To apply C Language to edit the bottom-driver code (namely TFT colorized screen driver, touch screen driver, motor driver, and various sensor drivers), GSM module communication code, and multi-layer interactive menu code by using STM32-SCM;
Outcome - established the demo system for smart windows.
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- Supervised by Prof. JiCai DENG Dec. 2013-Mar. 2014
Goal - to store and update control orders and display executive results; to send instructions to LED dot-matrix screen through the serial interface;
Tasks –
1. To design and realize the data transmission protocol between the upper monitor and handle control terminal;
2. To apply C Language to edit the bottom-driver code (namely 12864 LCD driver, button driver, serial port driver, and Flash driver by SPI bus), control function code, and multi-layer interactive menu code by using STC12-SCM;
Outcome - published paper Design of The Control Handle for LED Display Screen Based on SCM (2nd Author), Journal of Henan Science and Technology (ISSN1003-5168), April 2014.