3D-Printed Phase-Change Artificial Muscles with Autonomous Vibration Control

Currently, additive manufacturing is utilized to fabricate many different actuators suited for soft robots. However, an effective controller paradigm is essential to benefit from the advantages of soft robots in terms of power consumption, production costs, weight, and safety while operating near living systems. In this work, an artificial muscle is additively manufactured with soft silicone elastomer material capable of demonstrating several levels of stiffness. The 3D-printed muscle is equipped with carbon fibers to receive a stimulus signal and develop a programmable joint that can present different stiffnesses. A nonlinear controller is developed to autonomously control the variable stiffness joint based on a reinforcement learning algorithm. The controller exhibits a slight increase in settling time; however, it demonstrates a decrease in fluctuation amplitude by 33% and a substantial reduction in power consumption by 41% in comparison to the optimized proportional integral derivative controller. At the same time, it is adaptable to and reliable in new conditions. The variable stiffness muscle is also used as a controllable mechanism to suppress the low frequency vibration. The study shows that the muscle can successfully attenuate the vibration autonomously when it is increased.

Automated summary

Currently, additive manufacturing is used to fabricate various actuators for soft robots. An effective controller is required to take advantage of soft robots in terms of power consumption, production costs, weight, and safety when operating near living systems. This study develops an artificial muscle using soft silicone elastomer material that can demonstrate multiple levels of stiffness. A reinforcement learning algorithm-based nonlinear controller is designed to autonomously control the variable stiffness joint. The controller shows a slight increase in settling time but reduces fluctuation amplitude by 33% and power consumption by 41%, compared to the optimized proportional integral derivative controller. It is also adaptable and reliable in new conditions, and the variable stiffness muscle can attenuate vibrations autonomously when increased.