Chao (Frank) Xie
Academic Profile
Chao Xie

Chao (Frank) Xie

Ph.D. Student · University of Florida

I research automation in construction with AI and robotics, intelligent design methods, computer vision for 3D perception, and autonomous robotic systems for smarter, more efficient, safer, and scalable building processes.

News

  • Feb 2026

    Published Advancing Robotic Automation in Wood-Framed Construction Using Vision-Driven Adaptive Control published in Automation in Construction. DOI → Dataset →

  • Feb 2026

    Dataset Released Released WFC Dataset — a high-resolution, high-fidelity benchmark dataset capturing real-world wood-frame construction scenes, with peer benchmark results. GitHub →

Advanced Robotics & Embodied AI

My research focuses on vision-driven closed-loop robotic systems for real-world manipulation and assembly, with a specific emphasis on construction-scale tasks. By integrating 6D pose estimation, pose-based visual servoing (PBVS), and reinforcement learning across both task planning and motion planning layers, the developed systems achieve high-precision execution under real-world uncertainty — including occlusion, geometric variability, and unstructured environments. My work emphasizes seamless sim-to-real transfer of intelligent policies from high-fidelity digital twins to large-scale industrial workstations.

Looking ahead, I am exploring how Vision-Language-Action (VLA) models can serve as high-level semantic planners to further extend these systems toward open-vocabulary instruction following and broader generalization — with the goal of enabling autonomous, high-precision assembly of large-scale architectural structures.

Featured Projects

Upcoming Article

Full-Stack Closed-Loop Robotic Assembly System for Wood-Framed Construction

Demo of an in-progress full-stack system integrating RGB-D enhancement, 3D reconstruction, digital twin alignment, vision servoing, RL-based adaptive control, and real-time error correction for automated construction assembly.

Watch on YouTube →

Journal · Automation in Construction

High-Precision Real-Time Computer Vision 6-DoF Pose Estimation Algorithm Demo

Advancing Robotic Automation in Wood-Framed Construction Using Vision-Driven Adaptive Control

Watch on YouTube →

Education

  • University of Florida · Gainesville, FL Expected May 2027

    Ph.D. in Design, Construction and Planning · GPA: 3.97

    Full Scholarship & Graduate Assistantship

    Research: AI and robotics in construction, intelligent design methods, 3D perception, autonomous robotic systems.

  • University of Florida · Gainesville, FL Dec 2023

    M.S. in Construction Management · GPA: 4.00

    Full Scholarship & Graduate Assistantship  ·  Academic Excellence Award — top graduate of the cohort

  • Southwest Jiaotong University · Chengdu, China Jun 2013

    B.E. in Environmental Engineering

    B.E. in Economics (International Economics and Trade)

Awards & Honors

  • Rinker School Building Construction Scholarship Fall 2025

  • Impressive First — UF Coding Competition (Hackathon) Fall 2025

  • Ingle Family Scholarship Spring 2025

  • Rinker School Building Construction Scholarship Spring 2025

  • Phi Kappa Phi Honor Society Spring 2025

  • Jimmie Hinze Graduate Scholarship Fall 2024

  • CM Masters / Graduate Academic Excellence Award Fall 2023

    1 recipient · University of Florida

  • Sigma Lambda Chi (ΣΛΧ) International Construction Honor Society Fall 2023

Research Interests

  • Embodied AI & VLA Models: Developing Vision-Language-Action architectures that bridge high-level semantic reasoning with low-level motor control for generalizable task planning.
  • 3D Scene Understanding for Action: Engineering robust 6DoF object pose estimation and tracking algorithms using RGB-D data and point cloud geometry to enable precise manipulation.
  • Active Perception & Object-level Reasoning: Leveraging geometric constraints and semantic priors to resolve state estimation under heavy occlusion and environmental uncertainty.
  • Closed-loop Visual Servoing: Implementing adaptive control laws and real-time feedback loops for precision-critical assembly and construction-scale tasks.
  • Robotic Assembly under Uncertainty: Addressing complex challenges in symmetry, tight tolerances, and imperfect components through perception-action coupling.
  • Perception-Planning-Execution Co-design: Architecting integrated systems that ensure reliable deployment on large-scale industrial workstations.
  • Digital Twins & Sim-to-Real Pipelines: Building high-fidelity simulations to facilitate the scalable development and transfer of intelligent robotic policies.

Selected Publications

Conference | ConIC 2026

Quantitative Analysis of the Role of Robotics in Promoting Industrialized Construction for Resilient Post-Disaster Recovery: Exploratory Research

ConIC, 2026

Conference | I3CE 2026

Digital Twin-Enabled Adaptive Control for Perception-Driven Robotic Assembly in Industrialized Construction

I3CE, 2026

Conference | CRC 2026

Bridging the Gap: A Framework for Robotics Education in Industrialized Construction

ASCE Construction Research Congress (CRC), 2026

Teaching

  • BCN4612C — Construction Estimating 2

    Instructor · Taught every semester

  • BCN5905 — Advanced Construction Technology (Autodesk-Funded Course)

    Course Creator and Instructor

Contact

I welcome collaboration and invited talk opportunities.

Location Gainesville, FL 32603