TY - GEN
T1 - Modeling and Analysis of Dynamic Electrostatic Adhesion Based on Triboelectric Nanogenerators
AU - Qin, Ao
AU - Peng, Jun
AU - Zhu, Boshi
AU - Yuan, Kanglong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Electrostatic adhesion is emerging as a promising mechanism for wall-climbing robots to achieve both adhesion and detachment. Although numerous studies have investigated the gait and structure of these robots, the adhesion mechanism remains controlled by an external voltage source, which increases the weight and wiring burden. Additionally, high adhesion typically requires high voltage. To address these issues, this paper proposes a dynamic electrostatic adhesion model for the first time. The adhesive force is entirely generated by the contact-separation movement between the adhesive footpads and the substrate. We developed a theoretical model to elucidate the generation of electrostatic adhesion. By combining multiple parameters into dimensionless variables, we identified optimal conditions using only two parameters to predict optimal adhesion, thereby guiding the parameter design of dynamic electrostatic adhesion. Furthermore, we found that the electrical energy dissipated by resistance is equal to the negative work done by adhesion in one cycle, offering a theoretical basis for measuring the adhesion force.
AB - Electrostatic adhesion is emerging as a promising mechanism for wall-climbing robots to achieve both adhesion and detachment. Although numerous studies have investigated the gait and structure of these robots, the adhesion mechanism remains controlled by an external voltage source, which increases the weight and wiring burden. Additionally, high adhesion typically requires high voltage. To address these issues, this paper proposes a dynamic electrostatic adhesion model for the first time. The adhesive force is entirely generated by the contact-separation movement between the adhesive footpads and the substrate. We developed a theoretical model to elucidate the generation of electrostatic adhesion. By combining multiple parameters into dimensionless variables, we identified optimal conditions using only two parameters to predict optimal adhesion, thereby guiding the parameter design of dynamic electrostatic adhesion. Furthermore, we found that the electrical energy dissipated by resistance is equal to the negative work done by adhesion in one cycle, offering a theoretical basis for measuring the adhesion force.
KW - Electrostatic Adhesion
KW - Triboelectric Nanogenerators
KW - Wall-climbing Robots
UR - https://www.scopus.com/pages/publications/85218450583
U2 - 10.1007/978-981-96-0780-8_30
DO - 10.1007/978-981-96-0780-8_30
M3 - 会议稿件
AN - SCOPUS:85218450583
SN - 9789819607792
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 418
EP - 428
BT - Intelligent Robotics and Applications - 17th International Conference, ICIRA 2024, Proceedings
A2 - Lan, Xuguang
A2 - Mei, Xuesong
A2 - Jiang, Caigui
A2 - Zhao, Fei
A2 - Tian, Zhiqiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th International Conference on Intelligent Robotics and Applications, ICIRA 2024
Y2 - 31 July 2024 through 2 August 2024
ER -