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.

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Modeling and Analysis of Dynamic Electrostatic Adhesion Based on Triboelectric Nanogenerators

  • Ao Qin,
  • Jun Peng,
  • Boshi Zhu,
  • Kanglong Yuan

摘要

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.