Electroadhesion (EA), as an electrostatically driven, controllable adhesion technology, has unique attributes such as low noise, robust adaptability, and energy efficiency. However, its adhesion pressure is still low (0.1~10kPa) which may significantly limit its applications. This paper presents an innovative electroadhesion pad embedded with liquid and solid dielectrics. The experiments demonstrate that this liquid-solid electroadhesion pad (LSEAP) is capable of much larger adhesion pressure, compared to the traditional solid electroadhesion pad (SEAP). On one hand, the LSEAP can increase the dielectric contact with the substrate. On the other hand, the actuator can increase its dielectric strength. We also explore the application of this actuator to perching of a commercial Unmanned Aerial Vehicle (UAV), in order to promote the UAV's sustainable flight. Notably, the untethered LSEAP system, with an adhesion area as small as 4 cm2and a self-weight as light as 8.7 g, can support an UAV of 249.7 g for stable adhesion on various surfaces. The adhesion pressure generated by our LSEAD can be 32.2kPa, significantly larger than those reported in the literature. The weight ratio of the UAV to the LSEAP system is 14.6, more than double those in previous studies. The integration of this EA system markedly prolongs the operational duration of UAVs, rendering them suitable for sustainable surveillance and reconnaissance missions. This LSEAP also marks a pivotal advancement towards adhesion-based applications such as grippers and wall-climbing robots.

Soft robots and smart materials have seen rapid advancements in recent years, with significant potential applications in medical devices. Liquid crystal elastomers (LCEs) exhibit unique attributes of large deformations and diverse actuation modes, facilitating controllable bending in soft medical catheters and thereby enhancing their maneuverability during medical procedures. However, LCEs exhibit strong hysteresis, which makes their modeling and control challenging. In this paper, we develop a dynamic model of a light-stimulated LCE to describe its nonlinear time-dependent behavior. We first derive the relationship between the input laser power and the resulting temperature change of the LCE actuator, and then analyze the viscoelastic behavior by taking advantage of a spring-dashpot frame. For both the linear contraction actuator and the bending actuator, the dynamic equations can describe their behavior with acceptable errors. In the future, we will further test the LCE-based bending actuator of optimal design, and then perform real-time control of soft catheters with assistance of LCE actuators.

Soft pneumatic actuators can accomplish various customizable deformation/motion through the distribution of cavities and gradients in stiffness. However, traditional manufacturing methods, say molding, struggle to produce soft actuators with both complex cavities and desirable stiffness distributions. Regular 3D printing methods usually need extra printheads for support materials to fabricate soft actuators with cavities. In addition, the printing quality and fidelity of the whole structure cannot be uniform due to the effect of gravity, especially for a soft actuator with overhang features. To fabricate a soft actuator of uniform fidelity but desirable stiffness distributions, we propose an embedded 3D printing approach with only one active mixing printhead. By adjusting the mixing ratio of the dual-component silicone, we can achieve designated stiffness gradients, ranging from 30.2 kPa to 198 kPa. With this approach, we successfully fabricate soft pneumatic actuators with overhang features, which exhibit programmable elongation and radial expansion. Additionally, we fabricate soft bending actuators which can achieve programmable workspaces due to their predetermined stiffness distribution.

Dielectric elastomer actuators (DEAs) have been widely employed to drive various soft robots, due to their quiet fast muscle-like behavior. It is significant but challenging to model and control these soft actuators, due to their viscoelastic property, irregular geometry, complex structure, etc. In this paper, we propose a data-driven sparse identification method to discover the hidden governing equations of DEAs. These equations can help us interpret the nonlinear properties of DEAs. Due to their low computational cost, we can further use these equations to explore classic model-based control methods for real-time accurate control of viscoelastic DEAs. The experiments show that the proposed method can model the viscoelastic behavior of the DEAs with reasonable accuracy. A feedforward controller is finally developed to validate the effectiveness of the proposed method. It is expected that this modeling method can pave the way for accurate control of soft actuators/robots with structural and material nonlinearities.

Natural eyeball motions in humanoid robots can contribute to friendly communication, thus improving the human-robot interaction. In this paper, we develop antagonist-agonist artificial muscles for humanoid eyeball motions, by using dielectric elastomer actuators (DEAs). Inspired by human eyeballs, the artificial muscles consist of two pairs of DEA: one pair for the horizontal motion, and the other for the vertical motion. The fabrication time of actuators can be significantly decreased due to their simple structure. The antagonist-agonist actuator outperforms the dielectric elastomer minimum energy structure in terms of actuation displacement and response time. We conduct experiments in a lifesize human face model. The experiments demonstrate the capability of antagonist-agonist artificial muscles to mimic eyeball motions in the horizontal, vertical, and diagonal directions. Future work includes modeling and control of artificial muscles for optimal performance of various humanoid eyeball motions.