Yinxiao Li

About

Yinxiao Li is a robotics researcher whose work centers on the perception and manipulation of deformable objects, with a particular focus on garment handling and autonomous robotic systems. His most influential contributions address one of robotics' most persistent challenges: enabling robots to reliably recognize, track, and manipulate flexible, unstructured materials such as clothing. Li's highly cited 2015 work on folding deformable objects (107 citations) introduced predictive simulation and trajectory optimization to guide robotic arms through garment-folding tasks while minimizing wrinkles—a significant leap forward in dexterous manipulation. Complementing this, his research on regrasping and unfolding garments (60 citations) demonstrated how iterative regrasping strategies could bring garments from unknown to known states, and his multi-sensor ironing work extended these ideas to wrinkle detection and removal. His 2014 paper on volumetric pose estimation (69 citations) provided a real-time solution for tracking deformable objects using affordable depth sensors like the Kinect, broadening accessibility for robotic perception research. Earlier work on mobile robot navigation, including floor segmentation from single images (56 citations), highlights the breadth of Li's contributions to practical robotics. Collectively, his publications have garnered over 300 citations, establishing him as a meaningful contributor to robot learning and physical manipulation research.

Research Focus

Key Achievements

Top Papers

1. 1
   Folding deformable objects using predictive simulation and trajectory optimization

   107 citations · 2015
2. 2
   Real-time pose estimation of deformable objects using a volumetric approach

   69 citations · 2014
3. 3
   Regrasping and unfolding of garments using predictive thin shell modeling

   60 citations · 2015
4. 4
   Image-based segmentation of indoor corridor floors for a mobile robot

   56 citations · 2010
5. 5
   Model-Driven Feedforward Prediction for Manipulation of Deformable Objects

   39 citations · 2018
6. 6
   Multi-sensor surface analysis for robotic ironing

   36 citations · 2016
7. 7
   Visual detection of lintel-occluded doors by integrating multiple cues using a data-driven Markov chain Monte Carlo process

   9 citations · 2011
8. 8
   Folding Deformable Objects using Predictive Simulation and Trajectory Optimization

   9 citations · 2015
9. 9
   Model-Driven Feed-Forward Prediction for Manipulation of Deformable Objects

   6 citations · 2016
10. 10
    Multi-Sensor Surface Analysis for Robotic Ironing

    4 citations · 2016

Key Collaborators

Contact & Links