Pokuang Zhou

Second-year Ph.D. student in Robotics at Purdue University, advised by Professor Yu She.

Previously earned Bachelor's and Master's degrees in Engineering from Huazhong University of Science and Technology, advised by Academician Han Ding and Prof. Huan Zhao.

email
G. scholar
github

Research

Research during PhD stage. Research focuses on multimodal robot learning, robotic in-hand manipulation, embodied AI and control theory.

* indicates equal contribution.

Base on Issac Gym bulid a opensource platfrom. ManiFeel is a reproducible and scalable simulation benchmark for studying supervised visuotactile policy learning.

We developed a custom 5-DOF gripper that integrates both hardware design and control algorithms, enabling in-hand singulation, scooping, and cable untangling.

A Control Barrier Function based framework for Safe Human-Robot Collaboration that enables adjustable risk modulation to trade off between safety and task efficiency.

In a reinforcement learning framework, tactile feedback is used to control the aerial spinning motion of darts with varying mass, length, and deformability, enabling them to accurately hit targets at different distances.

TacScope is a miniaturized vision-based tactile sensor for surgical applications

StickRoller achieves precise in-hand stick repositioning through a sample-efficient tactile model. It enables the stick to be rolled to the center of the fingers using only a few well-planned two-finger manipulations.

In-Hand Singulation, Scooping, and Cable Untangling with a 5-Dof Tactile-Reactive Gripper

Robotic System with Tactile-Enabled High-Resolution Hyperspectral Imaging Device for Autonomous Corn Leaf Phenotyping in Controlled Environments

Miscellanea

Feel free to steal this website's source code. Do not scrape the HTML from this page itself, as it includes analytics tags that you do not want on your own website — use the github code instead. Also, consider using Leonid Keselman's Jekyll fork of this page.