Quan Luu

Profile Photo

Quan Khanh Luu

I will join the Department of Electrical and Computer Engineering (ECE) at the University of Nebraska–Lincoln (UNL) this Fall as an Assistant Professor, where I will lead research in robotics and physical embodied intelligence. Stay tuned for my lab website!

I’m looking for 1–2 passionate and highly motivated PhD students to join our team in Spring 2027 and Fall 2027. Please reach out if you’re interested!

I’m a postdoctoral researcher at Purdue University, working with Prof. Yu She and Prof. Qiang Qiu. I received my Ph.D. from the Japan Advanced Institute of Science and Technology (JAIST) in 2024, where I was advised by Prof. Van Anh Ho.

My research interests lie in creating soft and sensorized multimodal robotic bodies, especially those with a sense of touch, and leveraging them in robot learning and control systems. This work aims to enable robots to perform skilled and flexible manipulation, particularly in scenarios where contact and safe interaction with objects and surroundings are crucial.

My Curriculum Vitae can be found here.

News

  • [new] [Jun, 2026] I will join the ECE Department at UNL this Fall as an Assistant Professor in robotics and physical embodied intelligence. Stay tuned for my lab website!
  • [new] [Jun, 2026] ManiFeel won the Best Paper Award at the Sense of Touch Workshop at CVPR 2026! 🏆
  • [new] [Mar, 2026] Excited to share that our group has been awarded the NVIDIA Academic Grant Program to advance research in tactile-centric robot learning.

Selected Publications

(* indicates equal contribution)

ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning

Quan Khanh Luu*, Pokuang Zhou*, Zhengtong Xu*, Zhiyuan Zhang, Qiang Qiu, Yu She

under review, 2026

[arXiv] [Website] [Video]

ManiFeel presents a reproducible and scalable simulation benchmark for studying supervised visuotactile policy learning.

Vision-based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control

Quan Khanh Luu, Dinh Quang Nguyen, Nhan Huu Nguyen, Nam Phuong Dam, Van Anh Ho

IEEE Transaction on Robotics (T-RO), 2025

[Paper] [Code] [Website] [Video] [BibTex]

Based on our previous work on ProTac, this study enhances its multi-modal sensing performance and control integration for safer, more versatile robot operation in contact-rich environments.

Vi2TaP: A Cross-Polarization Based Mechanism for Perception Transition in Tactile-Proximity Sensing with Applications to Soft Grippers

Nhan Huu Nguyen, Nhat Minh Dinh Le, Quan Khanh Luu, Tuan Tai Nguyen, Van Anh Ho

IEEE Robotics and Automation Letters (RA-L), 2025

[Paper] [Video] [BibTex]

This study introduces Vi2TaP, a cross-polarization-based multimodal soft gripper that seamlessly switches between tactile and proximity sensing.

TacLink-Integrated Robot Arm toward Safe Human-Robot Interaction

Quan Khanh Luu, Alessandro Albini, Perla Maiolino, Van Anh Ho

IROS 2024

[Paper] [Code] [Video] [BibTex]

This study explores the use of TacLink, a soft vision-based tactile link, as a safety control mechanism that can potentially replace conventional rigid robot links and impact observers.

ConTac: Continuum-Emulated Soft Skinned Arm with Vision-based Shape Sensing and Contact-aware Manipulation

Tuan Tai Nguyen, Quan Khanh Luu, Dinh Quang Nguyen, Van Anh Ho

RSS 2024

[Paper] [Code] [Website] [Video] [BibTex]

This study introduces ConTac, a vision-based tactile sensing system for continuum-emulated robot arms with soft skin, enabling posture and contact detection.

Simulation, Learning, and Application of Vision-Based Tactile Sensing at Large Scale

Quan Khanh Luu, Nhan Huu Nguyen, Van Anh Ho

IEEE Transaction on Robotics (T-RO), 2023

[Paper] [Code] [Video] [BibTex]

This study introduces SimTacLS, a physics-informed simulation and learning pipeline designed for large-area soft vision-based tactile sensors.

Soft Robotic Link with Controllable Transparency for Vision-based Tactile and Proximity Sensing

Quan Khanh Luu, Dinh Quang Nguyen, Nhan Huu Nguyen, Van Anh Ho

IEEE RoboSoft 2023

[Paper] [Code] [Website] [Video] [BibTex]

This study presents ProTac, a novel soft robotic link with integrated tactile and proximity sensing.

Tombo Propeller: Bioinspired Deformable Structure Toward Collision-Accommodated Control for Drone

Son Tien Bui, Quan Khanh Luu, Dinh Quang Nguyen, Nhat Minh Dinh Le, Giuseppe Loianno, Van Anh Ho

IEEE Transaction on Robotics (T-RO), 2023

[Paper] [Code] [Website] [Video] [BibTex]

This study introduces Tombo, a soft deformable propeller, and demonstrates a control strategy enabling drones with Tombo to recover from midair collisions and resume flight.

A 3-Dimensional Printing System Using an Industrial Robotic Arm

Quan Khanh Luu, Hung Manh La, Van Anh Ho

IEEE/SICE SII 2021

[Paper] [Video] [BibTex]

This study introduces robot-assisted 3D printing on complex surfaces, paving the way for seamless human-robot collaboration in interactive manufacturing.

Wet Adhesion of Micro-patterned Interfaces for Stable Grasping of Deformable Objects

Pho Van Nguyen, Quan Khanh Luu, Yuzuru Takamura, Van Anh Ho

IROS 2020

[Paper] [Video] [BibTex]

Inspired by tree frogs, this study showcases a micro-patterned soft gripper pad that enables stable, damage-free manipulation of wet deformable objects in robotic food handling.

Honors

Teaching & Mentoring Experience

  • Guest Lecturer, IE474 – Industrial Control Systems, Purdue University, Oct 2025
  • Teaching Assistant (Voluntary), IE474 – Industrial Control Systems, Purdue University, Fall 2025
  • Teaching Assistant, M425E – Analytical Mechanics, JAIST, Fall 2021
  • Minor Research Advisor, JAIST, Apr 2022 – Dec 2022

Professional Service