Due to their continuous electromechanical deformation, rate-dependent viscoelasticity, and complex mechanical vibration, dynamic modeling and high-speed tracking control of dielectric elastomer actuators (DEAs) remain elusive, significantly limiting their working bandwidth. In this work, we propose a Physics-Informed Token Prediction (PITP) that enables accurate modeling of DEA dynamics and high-speed feedforward tracking control. The PITP framework consists of two key components: a physics-informed encoder and a dynamic decoder. The physics-informed encoder is designed based on a simplified equivalent linear model and trained through the hierarchical optimization training method, which embeds the global dynamic characteristics into tokens, minimizing the need for extensive data and training. Then, the dynamic decoder is developed by using these tokens as state-dependent parameters, capable of describing complex dynamic responses through the autoregressive solution. Finally, by taking advantage of the model's reversibility, a direct inverse compensator is established to linearize the input-output relationship. Experimental results of several DEAs with different configurations and payloads demonstrate that, based on our PITP framework, the complex nonlinear dynamic responses of all DEAs can be precisely described and eliminated within their natural frequency, validating its generality and versatility. By leveraging fast modeling ($< $30 minutes) and high-speed feedforward tracking control, our PITP framework may accelerate DEAs' practical applications.

Although many soft robots, capable of crawling or climbing, have been well developed, integrating multimodal locomotion into a soft robot for transitioning between crawling and climbing still remains elusive. In this work, we present a class of inchworm-inspired multimodal soft crawling-climbing robots (SCCRs) that can achieve crawling, climbing, and transitioning between horizontal and vertical planes. Inspired by the inchworm’s multimodal locomotion, which depends on the “$\Omega$” deformation of the body and controllable friction force of feet, we develop the SCCR by 1) three pneumatic artificial muscles based body designed to produce “$\Omega$” deformation; 2) two negative pressure suckers adopted to generate controllable friction forces. Then a simplified kinematic model is developed to characterize the kinematic features of the SCCRs. Lastly, a control strategy is proposed to synchronously control the “$\Omega$” deformation and sucker friction forces for multimodal locomotion. The experimental results demonstrate that the SCCR can move at a maximum speed of 21 mm/s (0.11 body length/s) on horizontal planes and 15 mm/s (0.079 body length/s) on vertical walls. Furthermore, the SCCR can work in confined spaces, carry a payload of 500 g (about 15 times the self-weight) on horizontal planes or 20 g on vertical walls, and move in aquatic environments.