硕 导 个 人 简 介

u 个人简介

彭彦鸿，讲师，硕士生导师。IEEE 机器人与自动化协会 (IEEE RAS) 会员， 日本机械学会 (JSME) 会员，日本文部科学省卓越大学院奖学金（2020.04-2024.03）获得者。2015.09-2019.07，获得北京交通大学机械电子工程学士学位；2018.01-2019.07，获得澳大利亚伍伦贡大学机械电子工程学士学位；2019.10-2021.09，获得日本名古屋大学机械系统工程硕士学位 （师从日本工程院外籍院士 巨阳教授）；2021.10-2024.03，获得日本名古屋大学信息通信工程博士学位；2022.04-2022.08，日本东京工业大学（今东京科学大学）特别访问学者；2024.04-至今，重庆理工大学机械工程学院教师。在国内外重要刊物如《Biomimetic Intelligence and Robotics》、《Sensors and Actuators A: Physical》等发表论文10余篇；在国际机器人会议发表4次（其中顶级会议IROS及ICRA各1次）。担任SCI期刊《Actuators》客座编辑和《Robotics》主题顾问委员会成员。作为审稿人参与了多本国际顶级期刊与会议的评审工作，包括《Expert Systems With Applications》、《Alexandria Engineering Journal》、《Biomimetic Intelligence and Robotics》、《Frontiers in Neurorobotics》、顶会IEEE IROS 2024、国际机器人会议IEEE ROBIO 2023等，发表论文共被他人引用240余次。

u 研究领域

仿生机器人，软体机器人，可穿戴软机器人，点云建模，深度学习，气动人工肌肉。

u 承担的主要项目

[1] 基于McKibben人工肌肉的仿生软体机器人研究，重庆理工大学科研启动基金，2024.4-2027.3，20万，主持。

[2] 基于McKibben人工肌肉的可穿戴布状执行器研究，名古屋大学前沿次世代项目研究者基金，2023，13万，主持。

[3] 控制人体运动和触觉的可穿戴有源设备研究，日本科学技术振兴机构FOREST基金，2022-2024，100万，参与。

[4] 基于体内控制论化身构建时空内部环境信息研究，日本科学技术振兴机构登月研发计划基金，2022-2025，金额保密，参与。

u 代表性成果

[1] Y. Peng*, Y. Wang, F. Hu, M. He, Z. Mao, X. Huang and J. Ding, “Predictive modeling of flexible EHD pumps using Kolmogorov–Arnold Networks,” Biomimetic Intelligence and Robotics, vol. 4, no. 4: 100184, 2024

[2] Y. Peng*, H. Nabae, Y. Funabora and K. Suzumori, “Controlling a Peristaltic Robot Inspired by Inchworms”, in Biomimetic Intelligence and Robotics, vol. 4, no. 1: 100146, 2024 (封面论文)

[3] Y. Peng*, H. Nabae, Y. Funabora and K. Suzumori, “Peristaltic Transporting Device Inspired by Large Intestine Structure”, in Sensors and Actuators A: Physical, vol. 365, p. 114840, 2024

[4] Y. Peng*, Y. Sakai, K. Nakagawa, Y. Funabora* et al., “Funabot-Suit: A Bio-Inspired and McKibben Muscle-Actuated Suit for Natural Kinesthetic Perception,” in Biomimetic Intelligence and Robotics, vol. 3, no. 4: 100127, 2023

[5] Y. Peng*, D. Li, X. Yang, Z. Ma and Z. Mao, “A Review on Electrohydrodynamic (EHD) Pump,” in Micromachines, vol. 14, no. 2: 321, 2023

[6] Y. Peng*, H. Yamaguchi, Y. Funabora* and S. Doki, "Modeling Fabric-Type Actuator Using Point Clouds by Deep Learning," in IEEE Access, vol. 10, pp. 94363-94375, 2022

[7] X. Bai †, Y. Peng †, D. Li, Z. Liu, and Z. Mao*, “Novel soft robotic finger model driven by electrohydrodynamic pump”, in Journal of Zhejiang University-SCIENCE A, vol. 25, pp. 596–604, 2024

[8] Z. Mao*, Y. Peng, C. Hu, R. Ding, “Soft computing-based predictive modeling of flexible electrohydrodynamic pumps,” in Biomimetic Intelligence and Robotics, vol. 3, no. 3: 100114, 2023

[9] Z. Ding, Y. Sun, S. Xu, Y. Pan, Y. Peng*, and Z. Mao, “Recent Advances and Perspectives in Deep Learning Techniques for 3D Point Cloud Data Processing,” in Robotics, vol. 12, no. 4: 100, 2023

[10] C. Zhang, J. Chen, J. Li, Y. Peng*, Z. Mao*, “Large language models for human-robot interaction: A review,” in Biomimetic Intelligence and Robotics, vol. 3, no. 4: 100131, 2023

[11] Y. Peng*, Y. Sakai, K. Nakagawa, Y. Funabora*, T. Aoyama, K. Yokoe, and S. Doki, “Fabric Actuator Suit: Actuated Suit Producing Torso Motion Sensation,” Poster contribution in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023.

[12] Y. Peng*, H. Yamaguchi, Y. Funabora*, S. Doki, “Modeling the Fabric-type Actuator by Deep Learning on Point Clouds”, Poster contribution in The 2022 35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.

[13] Y. Sato, Y. Peng*, Y. Funabora*, S. Doki, “Funabot-Finger Cot: Bio-Inspired Worm Robot for Peristaltic Wave Locomotion and Tubular Structure Climbing”, in 2024 IEEE/SICE International Symposium on System Integration (SII), 2024.

[14] Z. Mao*, C. Hu, Y. Peng. “Studying electric-driven soft pumps using machine learning algorithms.”, Workshop contribution in International Workshop on Piezoelectric Materials and Applications in Actuators (IWPMA2022), 2022.

u 联系方式

E-mail：yp@cqut.edu.cn