Inchworms are a widely adopted bio-inspired model for soft crawling robots. Taking advantage of the good controllability of Shape Memory Alloy (SMA), this paper designs and manufactures an inchworm-inspired soft robot driven by SMA. Firstly, in the structural design, the paper compares the heat dissipation performance and driving efficiency of SMA actuators with two assembly forms: embedded and external to the silicone body. The external structure assembly design with superior performance is chosen. Secondly, in the analysis of the motion characteristics of the soft robot, a kinematic model is developed. Addressing the issue of inaccurate representation in traditional constitutive models due to difficult-to-measure parameters, such as martensite volume fraction, this paper derives an exclusive new constitutive model starting from traditional models using methods like the Taylor series and thermodynamic laws. The kinematic model is simulated using the Simulink platform to obtain its open-loop step response and sinusoidal signal response. Finally, an experimental platform is set up to conduct crawling tests on the soft robot in different planes. The experimental results show that the inchworm-inspired soft robot can perform continuous crawling motion, with a crawling speed of 0.041 mm/s on sandpaper under a constant current of 4A.

The compressibility of air, the uncertainty of dynamic models, and the existence of friction make pneumatic servo systems exhibit strong nonlinearity. Furthermore, the confluence of pneumatic-system nonlinearity and interference from the position system induces oscillations within the system, thereby posing a formidable challenge for achieving precise torque control. This study ensures precise torque control in a pneumatic actuator amid interference from the position system and proposes a novel active disturbance-rejection controller integrated with a Kalman filter. Firstly, in response to the oscillation stemming from the inherent nonlinearity of the pneumatic system and interference from the position system, this paper designs an active disturbance-rejection controller (ADRC) with robust anti-interference capabilities aimed at mitigating system oscillations. Secondly, to address the issue of sensor noise interfering with the ADRC and causing system oscillation, a first-order Kalman filter is designed to provide real-time and more accurate state estimation, effectively reducing oscillations and improving the robustness of the system. Finally, using the Lyapunov stability theory, the effectiveness of both the nonlinear extended observer and the convergence of the nonlinear error-state controller in the ADRC is proven. Experimental results indicate that the proposed controller reduces system oscillations and improves control accuracy.