Shape memory alloys (SMAs) or shape memory polymers (SMPs) enable soft actuators to achieve advanced adaptabilities applied in soft robotics. However, actuators that combine multiple shape memory materials struggle to achieve complex deformation effects and stiffness variations with effective control strategies. To achieve controllable, shape adaptation, and programmed deforming behavior, this study proposes an integrated control strategy for an SMA-SMP based programmable morphing structure used as an actuator in soft robotics. To achieve precise control over programming deformations and stiffness variation, a multi-target thermal sensing method (MTTSM) was proposed, integrated into an interaction-driven control framework. Based on MTTSM, the coordinated actuation between the SMA springs and the SMP structure is realized, enabling standby of preheating, stepping with programmed deformations, and dynamic stiffness changes. In addition, to achieve dynamic monitoring of deformed states, the co-training-based monitoring system is developed for collaboration, enabling the use of multisensor fusion for position estimation in the absence of end-effectors that can directly measure the deformed structure of the flexible body. In conclusion, the proposed integration strategy of MTTSM and the cotraining monitoring system offers a control solution for integrating multiple shape memory materials into morphing structures as smart actuators applied to soft robotic applications.
Chen et al. (Mon,) studied this question.