2025

[16] Haoyang Wang, Haoran Guo, Zhengxiong Li, Lingfeng Tao, ’Adaptive Anomaly Recovery for Telemanipulation: A Diffusion Model Approach to Vision-Based Tracking .’ (Accepted by IROS2025)

[15] Haoran Guo, Haoyang Wang, Zhengxiong Li, Lingfeng Tao, ’Bio-Skin: A Cost-effective Thermostatic Tactile Sensor with Multi-Modal Force and Temperature Detection.’ (Accepted by IROS2025)

[14] Xinming Fang, Lingfeng Tao, Zhengxiong Li, ’Leveraging Virtual Reality for Large-Scale Robotic Manipulation Dataset Collection’. (Accepted by IROS2025)

[13] Xinming Fang, Lingfeng Tao, Zhengxiong Li, ’Learning to Grasp and Pour: Curriculum and Transfer Learning with Hierarchical Rewards and Proxy-Based Liquid Approximation.’ (Accepted by IROS2025)

[12] Zheshuo Li, Lingfeng Tao, Yidian Hu, and Zhengxiong Li. “PlasTrack: Path-Independent Plasma-Induced Attacks on mmWave Sensing Tracking.” In 2025 IEEE Conference on Communications and Network Security (CNS), pp. 1-9. IEEE, 2025.

[11] Fang, Xinmin, Hailu Xu, Lingfeng Tao, and Zhengxiong Li. “mmVanish: Extending the Vanish Attack for Multi-Radar Exploitation of mmWave Sensing with Meta-material Tags.” In Proceedings of the 2nd International Workshop on Security and Privacy of Sensing Systems, pp. 12-16. 2025. (Best Paper Award)

[10] Lingfeng Tao, Jiucai Zhang, and Xiaoli Zhang. “Stable In-Hand Manipulation with Finger-Specific Multi-Agent Shadow Critic Consensus and Information Sharing.” IEEE Robotics and Automation Letters (2025). vol. 10, no. 3, pp. 2407-2413, March 2025.

2024

[9] Wang, Haoyang, He Bai, Xiaoli Zhang, Yunsik Jung, Michel Bowman, and Lingfeng Tao. “Real-time Dexterous Telemanipulation with an End-Effect-Oriented Learning-based Approach.” In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 12164-12169. IEEE, 2024.

[8] Lingfeng Tao, Jiucai Zhang, Qiaojie Zheng, Xiaoli Zhang. ‘Curriculum-based Sensing Reduction in Simulation to Real-World Transfer for In-hand Manipulation.’ 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024.

2023

[6] Tao, Lingfeng, Jiucai Zhang, Michael Bowman, and Xiaoli Zhang. “A Multi-Agent Approach for Adaptive Finger Cooperation in Learning-based In-Hand Manipulation.” In 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 3897-3903. IEEE, 2023.

2022

[5] Tao, Lingfeng, Michael Bowman, Xu Zhou, Jiucai Zhang, and Xiaoli Zhang. “Learn and Transfer Knowledge of Preferred Assistance Strategies in Semi-Autonomous Telemanipulation.” Journal of Intelligent & Robotic Systems 104, no. 3 (2022): 1-16.

[4] Tao, Lingfeng, Jiucai Zhang, and Xiaoli Zhang. “Multi-Phase Multi-Objective Dexterous Manipulation with Adaptive Hierarchical Curriculum.” Journal of Intelligent & Robotic Systems 106, no. 1 (2022): 1-11.

2021

[3] Tao, Lingfeng, Michael Bowman, Jiucai Zhang, and Xiaoli Zhang. “Forming Real-World Human-Robot Cooperation for Tasks With General Goal.” IEEE Robotics and Automation Letters 7, no. 2 (2021): 762-769.

[2] Stanley, Matthew, Lingfeng Tao, and Xiaoli Zhang. “Robust Motion Mapping Between Human and Humanoids Using CycleAutoencoder.” 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2021.

[1] Tao, Lingfeng, Michael Bowman, Jiucai Zhang, and Xiaoli Zhang. “Learn Task First or Learn Human Partner First: A Hierarchical Task Decomposition Method for Human-Robot Cooperation.” In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 590-595. IEEE, 2021.