Hi, I am Fan Chen.

I am a thesis-track M.S. student in Mechanical Engineering at the University of Illinois Urbana-Champaign, advised by Prof. Naira Hovakimyan in the Advanced Controls Research Laboratory. Previously, I received my B.Eng. in Vehicle Engineering at the Tongji University under the supervision of Prof. Gang Niu. My research interests lie in the area of Robotics. My current research focuses on planning and control for autonomous aerial robots.

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I am seeking PhD opportunities for Fall 2026. Feel free to contact me!

Email: fanc3@illinois.edu

Research Interests

Selected Projects

Work Experience

Research Interests

Planning and Control: Designing efficient and robust planning and control algorithms for various robots, including aerial robots and ground robots.
Anomaly Detection: Developing anomaly detection and fault diagnosis technologies and algorithms to assist robots in completing tasks or ensure human safety.
Artificial Intelligence for Robots: Developing reinforcement learning and VLA models to enhance robots' ability to solve diverse and complex tasks.
Field Robots: Designing robotic systems tailored for diverse industrial environments, such as construction site inspection, exploration of unknown environments, and scene reconstruction.

Research

Reinforcement Learning for UAV Interception with Out-of-Distribution Targets (Current Research)

Jun. 2025 - present

Developing a reinforcement learning framework to improve the adaptive path planning of UAVs for pursuing out-of-distribution targets.

Real-Time Anomaly Detection and Emergency Path Planning During Drone Flight (Current Research)

Jun. 2025 - present

Investigating real-time anomaly detection algorithms to enable autonomous drones to more efficiently detect abnormal situations and respond to abnormal situations.
Applicable to construction site monitoring, rescue operations, and other tasks.

Motor Fault Diagnosis Method Based on the Fusion of Vibration and Current Signals (Undergraduate Thesis)

Oct. 2022 - Jun. 2023

Designed motor fault diagnosis methods based on current and vibration signals collected from both simulated and real-world motors.
Employed five advanced decision-level data fusion methods and adjusted the corresponding decision fusion algorithm to address the motor fault diagnosis problem.
Enhanced the motor fault diagnosis accuracy by 20 percentage points compared to the method based on current signals.
The original thesis is in Chinese. Its English abstract is here.

Selected Projects

Language-Guided Grasping in Clutter

Oct. 2025 - present

Developing a robotic system in Isaac Sim that identifies and grasps target objects in heavily cluttered scenes based on natural language commands.
The system will generate and execute collision-aware 6-DoF grasps, with a focus on evaluating robustness against significant object occlusion and varying levels of clutter.
Achieved a success rate of over 90% in initial testing

Affordable Robot with SLAM based on LiDAR

Feb. 2025 - Apr. 2025

Developed a low-cost robot for indoor mapping utilizing a LiDAR sensor and SLAM algorithm.
Achieved 94.52% accuracy by comparing the SLAM-generated map to real-world measurements.

Intelligent Construction Site Inspection Vehicle

Mar. 2024 - Jun. 2024

Designed a car that uses LiDAR and cameras to inspect the construction site along the preset route, and identify whether workers are wearing safety helmets.
Enabled the car to automatically adjust its speed based on the density of people and complexity of the terrain in different areas of the construction site.
Developed and implemented a fixed-point parking function, enabling precise location setting and customizable parking duration.

Indoor Localization System for Model Trains

Jan. 2022 - Oct. 2022

Developed an indoor ultra-wideband (UWB) localization system for model trains on a simulated sand table platform.

Other Robots

Before 2022

Quadruped Spider Robot
Autonomous Obstacle Avoidance and Tracking Car

Work Experience

Research Assistant (Advisor: Prof. Huawei Liang) - Hefei Institutes of Physical Science, Chinese Academy of Sciences

Sep. 2023 - Jun. 2024

Autonomous Driving Intern - IM Motors

Nov. 2022 - Feb. 2023

Contributed to the safety validation team for autonomous driving features, analyzing test data to identify and mitigate key reliability risks.
Contributed to the development of a novel anti-rear-end intelligent driving system, with the core technology filed for a patent.

Summer Intern - CRRC Zhuzhou Institute

Jul. 2022

Summer Intern - Shanghai Shentong Metro Group

Jul. 2022

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