Hantao Ye

I am going to join the University of Minnesota, Twin Cities this Fall as a Ph.D. student in ECE, and working with Dr. Changhyun Choi. Currently, I am a research assistant at RRoS Lab working on the robot control and simulation, advised by Dr. SK Gupta.

I graduated with a Master's degree in Computer Science from the University of Southern California in 2024. Prior to that, I received my Bachelor's degree in Mechatronics Engineering from Beijing Jiaotong University in 2022. During my undergraduate studies, I spent a year (2021-2022) as an exchange student at the National University of Singapore Research Institute (Suzhou), majoring in Mechanical Engineering.

I'm interested in robotics, deformable object manipulation, and robot learning.

Selected Publications

* represents equal contribution, listed alphabetically

Real-to-Sim Parameter Learning for Deformable Packages Using High-Fidelity Simulators for Robotic Manipulation

Omey M. Manyar^*, Hantao Ye^*, Siddharth Mayya, Fan Wang, Satyandra K. Gupta

preprint, 2025

[Project Page] [Paper] [Code]

Deformable packages are becoming increasingly prevalent in the logistics and warehouse industry, demanding robotic manipulation strategies that are robust and adaptive. In this work, we present a physics-driven simulation framework that accurately models multi-object deformable packages, capturing package deformations, suction-cup interactions, and internal object dynamics. By leveraging high-fidelity physics, we optimize simulation parameters using real-world trajectory and package deformation data, ensuring an accurate representation of package behavior.

Simulation-Assisted Learning for Efficient Bin-Packing of Deformable Packages in a Bimanual Robotic Cell

Omey M. Manyar^*, Hantao Ye^*, Meghana Sagare, Siddharth Mayya, Fan Wang, Satyandra K. Gupta

IROS, 2024

[Project Page] [Paper] [Code]

Bin-packing is an important problem in the robotic warehouse domain. Traditionally, this problem has been studied only for rigid packages (e.g., boxes or rigid objects). In this work, we tackle the problem of bin-packing with deformable packages that have become a popular choice for fulfillment needs. We present a system that incorporates a dual robot arm bimanual setup, uniquely combining suction and sweeping motions to stably and reliably pack deformable packages in a bin.

Selected Projects

YOLO-V8 Based Package Segmentation and Sorting

RRoS-Lab, USC

May 2023 - August 2023

[Demo]

We developed a bimanual robotic system that utilized two robots for package handling: one for placing packages into a bin and another for stowing them, achieving an 89% success rate in 100 trials. This system integrated the Yolo v8 object detection model with the MoveIt planning interface for precise package detection and handling. Additionally, I built an offline planning database that generated optimal robotic paths, enhancing the efficiency and reliability of the operation.