2025

[25] Xinyi Liu, Yidan Hu, Haoyang Wang, Lingfeng Tao, Zhengxiong Li, ‘Secure Real-time Dexterous Telemanipulation with Usability-Approve Privacy-Preserving’

[24] Zheshuo Li, Lingfeng Tao, Yidian Hu, Zhengxiong Li ‘PlasTrack: Path-Independent Plasma-Induced Attacks on mmWave Sensing Tracking.’ (Accepted by IEEE CNS 2025)

[23] 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).

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

[21] 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)

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

[19] 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)

[18] Zheshuo Li, Lingfeng Tao, Zhengxiong Li, A Lie Group-Integrated Framework for Sampling-Based Motion Planning of Robotic Manipulators.

2024

[17] Lingfeng Tao, et al. ‘You Only Render Once: Enhancing Energy and Computation Efficiency of Mobile Virtual Reality.’ (Anonymously Submitted)

[16] Lingfeng Tao, et al. ‘MetaVR: User Information Attack on User Motion Information through VR Video Clips.’ (Anonymously Submitted)

[15] Haoran Guo, Haoyang Wang, Zhengxiong Li, He Bai, and Lingfeng Tao, ‘Impact of Tactile Sensor Quantities and Placements on Learning-based Dexterous Manipulation.’ (Submitted to IEEE RAL)

[14] Haoyang Wang, Haoran Guo, He Bai, Zhengxiong Li, and Lingfeng Tao, ‘Bi-directional Momentum-based Haptic Feedback and Control System for Dexterous Telemanipulation.’(Submitted to IEEE RAL)

[13] 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.

[12]. Chulho Yang, Lingfeng Tao, and Avimanyu Sahoo, ‘New Programs in Mechatronics and Robotics: Curriculum Development, Status, and Direction for Engineering Technology.’(Submitted to CIEC2025)

[11]. Yunsik Jung, Lingfeng Tao, Michael Bowman, Jiucai Zhang, Xiaoli Zhang, ‘Risk-prioritized Experience Replay for Stable In-hand Manipulation.’(Submitted to ICRA 2025)

[10] 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. (H-Index 119)

2023

[9] Tao, Lingfeng, Jiucai Zhang, and Xiaoli Zhang. ”Stable In-hand Manipulation with Finger Specific Multi-agent Shadow Reward.” arXiv preprint arXiv:2309.07349

[8] 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. (H-Index 119)

2022

[7] 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. (H-Index 49, IF 3.3)

[6] 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. (H-Index 49, IF 3.3)

[5] Jung, Yunsik, Lingfeng Tao, Michael Bowman, Jiucai Zhang, and Xiaoli Zhang. “Physics-Guided Hierarchical Reward Mechanism for Learning-Based Multi-Finger Object Grasping.” arXiv preprint arXiv:2205.13561 (2022). (Submitted to IEEE RAL)

[4] Matthew Stanley, Yunsik Jung, Michael Bowman, Lingfeng Tao, and Xiaoli Zhang. “Transferability-based Chain Motion Mapping from Humans to Humanoids for Teleoperation.” arXiv preprint arXiv:2210.16423 (2022). (Submitted to Journal of Intelligent & Robotic Systems)

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. (H-Index 106, IF 5.79)

[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. (H-Index 19)

[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. (H-Index 32)