Portrait of Yongqiang Zhao

Yongqiang Zhao 赵永强

I am a PhD student in the Department of Engineering at King's College London. I work with Prof. Shan Luo and my research focuses on machine perception for robot interaction, especially visual-tactile perception for dexterous manipulation.
Before joining King's, I received both my Bachelor's and Master's degrees from Southeast University under the guidance of Prof. Kun Qian.

Recent News

Papers

Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly
Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Matteo Leonetti, Emmanouil Spyrakos Papastavridis, Shan Luo
IEEE Robotics and Automation Letters, 2026
ViTac-Tracing: Visual-Tactile Imitation Learning of Deformable Object Tracing
Yongqiang Zhao, Haining Luo, Yupeng Wang, Emmanouil Spyrakos Papastavridis, Yiannis Demiris, Shan Luo
IEEE International Conference on Robotics and Automation, accepted, 2026
ViTacGen preview
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
ConViTac: Aligning Visual-Tactile Fusion with Contrastive Representations
Zhiyuan Wu, Yongqiang Zhao, Shan Luo
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025
SimTac preview
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
GenForce preview
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
FOTS preview
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
Tubular manipulation preview
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
Pose estimation preview
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
ViTac workshop preview
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
APF-RRT preview
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 list updated using public records associated with your Google Scholar profile, primarily King's College London Pure entries when Scholar itself could not be fetched directly.

Projects

Tactile foundation models project
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 project
Visual-Tactile Imitation Learning of Deformable Object Manipulation
Mar. 2025 - Sep. 2025
Visiting researcher at the Personal Robotics Laboratory, Imperial College London, collaborating with Dr. Haining Luo, Prof. Yiannis Demiris, and Dr. Emmanuel Papastavridis.
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 project
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.