CV

Curriculum Vitae

Basics

Name Huoyuan Tan
Label PhD Student in Robotics
Email tanhuoyuan@gmail.com
Phone -

Work

  • 2017.02 - 2022.10

    Shenzhen, China

    Robotics Engineer
    Xingyun Intelligence (Shenzhen) Technology Co., Ltd.

    Developed and deployed algorithms for autonomous mobile robotic systems used in logistics, factory, and port automation.

    • Multi-sensor fusion (camera, LiDAR, GNSS/RTK, IMU), SLAM, perception, planning, control, and ROS-based system development in C++/Python.
    • Drove end-to-end delivery — from algorithm design and system integration to on-site deployment and fleet tuning — across hardware, software, and operations teams.

Education

  • 2026.10 - Present

    Gothenburg, Sweden

    Ph.D.
    Chalmers University of Technology

    Division of Systems and Control, Department of Electrical Engineering

    • Research focus: structured, interpretable, and experience-driven robot learning for resilient and adaptive behavior in collaborative robots
  • 2024.09 - 2026.06

    Gothenburg, Sweden

    M.Sc.
    University of Gothenburg

    Computer Science and Engineering

    • Thesis: Assessment & Failure Recovery in Remote Vision-Language-Action (VLA) Deployment
    • Supervisor: Ze Zhang | Examiner: Ahmed Ali-Eldin Hassan | Thesis partner: Yajing Zhang
    • Selected courses: Deep Machine Learning, Advanced Topics in Machine Learning, Design of AI Systems, Computational Semantics, Discrete Optimization, Advanced Algorithms
  • 2013.09 - 2017.06

    Guangzhou, China

    B.Eng.
    Guangzhou University of Chinese Medicine

    Medical Information Engineering

    • Thesis: The Application of Ensemble Learning in Quantitative Investment Prediction
    • Outstanding Graduate Award, 2017
    • Core courses: Data Structures & Algorithms, Java, C, Database Design, Networking, Operating Systems

Publications

Skills

Perception
2D/3D object detection & tracking
Semantic segmentation
Multi-camera & camera–LiDAR calibration
Multi-sensor fusion
Localization & SLAM
LiDAR graph-based SLAM, ICP/NDT
Cartographer, ORB-SLAM3
State estimation with EKF/UKF
Planning & Control
A*, Hybrid-A*, TEB
PID, MPC
Decision making & trajectory optimization
Machine Learning
PyTorch, Hugging Face
Deep learning for detection & segmentation
LLMs, VLA models, Reinforcement Learning
Programming & Tools
C++, Python
ROS / ROS2, Linux, CMake
Docker, Git
Hardware & Protocols
LiDAR, GNSS/RTK, IMU, Camera
CAN, Modbus, MQTT

Languages

Mandarin Chinese
Native speaker
Cantonese
Native speaker
English
Fluent — everyday and academic communication

Projects

  • 2025.11 - 2026.06
    M.Sc. Thesis — Assessment and Failure Recovery in Remote VLA Deployment

    Built a pipeline for deploying Vision-Language-Action (VLA) models remotely, with runtime monitoring and failure recovery for robot manipulation.

    • Remote deployment of VLA policies with robot-side execution
    • Runtime monitoring and assessment of task execution
    • Failure detection and recovery strategies
    • Evaluation in simulation and on a real robot
  • 2021.10 - 2022.10
    Autonomous Forklift

    An autonomous forklift system integrating onboard sensing, roadside infrastructure, and cloud services for automated truck loading and unloading.

    • Implemented LiDAR–camera calibration and sensor fusion.
    • Developed MPC-based motion planning for precise navigation.
    • Contributed to a system achieving 90–92% success rates in automated loading and unloading.
  • 2020.10 - 2022.10
    Intelligent Guided Vehicle (IGV) / Autonomous Port Truck (ART)

    An autonomous transport system for container transportation and port automation.

    • Implemented multi-LiDAR calibration and sensor fusion for mapping, localization, and perception.
    • Developed a LiDAR-based perception and decision-making module for obstacle avoidance.
    • Contributed to real-world port deployment, with a reported throughput of 35 containers per hour.
  • 2018.05 - 2020.05
    Automated Guided Vehicle (AGV)

    Automated guided vehicles for material transportation in factories.

    • Developed LiDAR–IMU graph-based SLAM with loop closure.
    • Implemented a fast initial localization module.
    • Developed map updating and extension capabilities.
    • Deployed the navigation system in indoor and outdoor factory environments.
  • 2015.06 - 2017.02
    Indoor Activity Recognition with Pyroelectric Infrared Sensors

    Developed a PIR sensor-based system for indoor tracking and activity monitoring to support older adults living independently.

    • Pyroelectric Infrared (PIR) sensor array with FOV modulation
    • Two-layer Random Forest classifier for tracking and activity recognition
    • Abnormal activity detection via HMMs and One-Class SVMs
    • Published in Sensors (MDPI), 2016 & 2017