Yuhe Fan

About

Yuhe Fan is a pioneering researcher at the intersection of robotics, computer vision, and food mechanics, with a primary focus on developing intelligent meal-assisting robotic systems for individuals with limited mobility. His work addresses the deeply complex challenge of enabling robots to autonomously and reliably handle food — a problem that demands expertise spanning multiple disciplines. Fan's most significant contributions lie in characterizing the physical behavior of food during robotic manipulation. His investigations into non-Newtonian fluid-solid food interactions, employing innovative coupled SPH-FEM computational methods, have illuminated the intricate contact forces that arise when a robotic spoon engages with complex food materials — foundational insights that have garnered over 24 citations across related studies. Complementing this mechanical work, he has advanced real-time computer vision capabilities for meal-assisting robots, developing high-accuracy instance segmentation and detection models for foods, faces, and mouth-opening states, collectively accumulating over 40 citations since 2024 alone. Fan's research portfolio reflects a rare and valuable integration of soft-matter physics, deep learning, and assistive technology design. His continued exploration of meal posture estimation and food volume measurement signals a trajectory toward fully autonomous, perception-driven robotic feeding systems with meaningful humanitarian applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Motion behavior of non-Newtonian fluid-solid interaction foods

   18 citations · 2023
2. 2
   Real-time and accurate meal detection for meal-assisting robots

   15 citations · 2024
3. 3
   Instance segmentation of faces and mouth-opening degrees based on improved YOLOv8 method

   11 citations · 2024
4. 4
   Viscoelasticity and friction of solid foods measurement by simulating meal-assisting robot

   10 citations · 2022
5. 5
   Real-time and accurate model of instance segmentation of foods

   9 citations · 2024
6. 6
   Real-time and accurate detection for face and mouth openings in meal-assisting robotics

   6 citations · 2024
7. 7
   Contact forces and motion behavior of non‐Newtonian fluid–solid food by coupled SPH–FEM method

   6 citations · 2023
8. 8
   Measuring posture and volume of meals for meal-assisting robotics

   3 citations · 2025

Key Collaborators

Contact & Links