Recent News

• [2026/03] Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly was published in IEEE Robotics and Automation Letters.
• [2026/03] ViTac-Tracing: Visual-Tactile Imitation Learning of Deformable Object Tracing was accepted by ICRA 2026.
• [2026/02] SimTac: A Physics-Based Simulator for Vision-Based Tactile Sensing with Biomorphic Structures was published in Cyborg and Bionic Systems.
• [2026/01] Training Tactile Sensors to Learn Force Sensing from Each Other was published in Nature Communications.
• [2025/Summer] I was a leading developer and organizer of the Third London Summer School in Robotics and AI, including the visual-tactile grasping mini-hackathon using LeRobot SO-ARM101.
• [2024/04] FOTS: A Fast Optical Tactile Simulator for Sim2Real Learning of Tactile-guided Robot Manipulation Skills was published in IEEE Robotics and Automation Letters.
• [2023/02] Skill Generalization of Tubular Object Manipulation with Tactile Sensing and Sim2Real Learning was published in Robotics and Autonomous Systems.

Papers

ViTacGen: Robotic Pushing with Vision-to-Touch Generation

Zhiyuan Wu, Yijiong Lin, Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Nathan Lepora, Shan Luo

IEEE Robotics and Automation Letters, accepted/in press, 2025

Paper Project Website

SimTac: A Physics-Based Simulator for Vision-Based Tactile Sensing with Biomorphic Structures

Xuyang Zhang, Jiaqi Jiang, Zhuo Chen, Yongqiang Zhao, Tianqi Yang, Daniel Fernandes Gomes, Jianan Wang, Shan Luo

Cyborg and Bionic Systems, 2026

Paper Code

Training Tactile Sensors to Learn Force Sensing from Each Other

Zhuo Chen, Ni Ou, Xuyang Zhang, Zhiyuan Wu, Yongqiang Zhao, Yupeng Wang, Emmanouil Spyrakos Papastavridis, Nathan Lepora, Lorenzo Jamone, Jiankang Deng, Shan Luo

Nature Communications, published January 28, 2026

Paper Project Website

FOTS: A Fast Optical Tactile Simulator for Sim2Real Learning of Tactile-guided Robot Manipulation Skills

Yongqiang Zhao, Kun Qian, Boyi Duan, Shan Luo

IEEE Robotics and Automation Letters, 2024

Paper Code Project Website Video

Skill Generalization of Tubular Object Manipulation with Tactile Sensing and Sim2Real Learning

Yongqiang Zhao, Xingshuo Jing, Kun Qian, Daniel Fernandes Gomes, Shan Luo

Robotics and Autonomous Systems, 2023

Paper Code Video

Pixel-Level Domain Adaptation for Real-to-Sim Object Pose Estimation

Kun Qian, Yanhui Duan, Chaomin Luo, Yongqiang Zhao, Xingshuo Jing

IEEE Transactions on Cognitive and Developmental Systems, 2023

Paper

Unsupervised Adversarial Domain Adaptation for Sim-to-Real Transfer of Tactile Manipulation Skills

Xingshuo Jing, Yongqiang Zhao, Jialun Jiang, Boyi Duan, Kun Qian, Shan Luo

ICRA 2023 ViTac Workshop

Paper

Path Planning of UAV Delivery Based on Improved APF-RRT* Algorithm

Yongqiang Zhao, Kai Liu, Gaohan Lu, Yuru Hu, Shuwen Yuan

International Conference on Computer Modeling, Simulation and Algorithm, 2020

Paper Code

Projects

Tactile Foundation Models for Robot Manipulation

Dec. 2025 - Present

Ongoing collaboration with Huawei Noah’s Ark Lab on foundation-model-style tactile representations for contact-rich robot manipulation.

Lead learning-method design and experimental validation for scalable pretraining objectives connecting tactile sensing, robot state, and visual observations.

Visual-Tactile Imitation Learning of Deformable Object Manipulation

Summer 2025

Visiting student at the Personal Robotics Laboratory, Imperial College London, working with Prof. Yiannis Demiris and Dr. Haining Luo.

Constructed a visual-tactile teleoperation system for ABB YuMi and introduced local/global task losses for robust tracing policies.

Tactile Simulation and Sim-to-Real Skill Learning

Jan. 2024 - Mar. 2026

Proposed a fast simulation algorithm for vision-based tactile sensors through learned optical rendering and efficient marker-motion approximation.

Developed a visual-tactile simulation suite in MuJoCo and supported sim-to-real policy learning via teacher-student training, domain randomization, and tactile image transfer.