Quan Khanh Luu
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, 2025] An abstract of the ManiFeel paper has been accepted to the COMPARE Workshop at RSS 2025. The work will be presented on June 25th, 2025, at USC in Los Angeles, USA.
- [new] [Jun, 2025] An abstract of the ManiFeel paper has been accepted for the oral presentation at New England Manipulation Symposium (NEMS 2025), MIT Stata Center, Cambridge, MA.
- [new] [Jun, 2025] Presented our latest ManiFeel paper at the 2025 Midwest Robotics Workshop at TTIC.
- [Oct, 2024] I am excited to begin a postdoctoral position at Purdue University, where I will continue my research on multimodal robotic perception and learning.
- [Aug, 2024] I successfully defended my PhD thesis, “Large-area Multimodal Soft Sensing Skin for Human-Robot Interaction”, at JAIST, Japan.
- [May, 2024] I am honored to be selected as part of the RSS Pioneers cohort and will attend the RSS Pioneers 2024 on July 14, 2024, at TU Delft, Delft, Netherlands.
- [Mar, 2024] I am honored to have been awarded the JSPS Research Fellowship for Young Scientists (DC2), which I am starting in April 2024.
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, 2025
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, conditionally accepted
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
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
[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
[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
[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
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
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
- JSPS Research Fellowship for Young Scientists (DC2), 2024
- RSS Pioneers Cohort, 2024
- Finalist, Best Paper Award, IEEE/SICE SII, 2024
- Outstanding Graduate Student Award, School of Materials Science, JAIST, 2021
Professional Service
- Program Committee Member: RSS Pioneers 2025
- Journal Reviewer: Nature Communications, IEEE T-RO, IEEE RA-L, Advanced Robotics
- Conference Reviewer: ICRA, IROS, RSS, CoRL, SII, Humanoids