An Embedded Proprioceptive Sensing Method for Soft Artificial Muscles With Tube-Fiber Structure

Soft artificial muscles have been used for wearable robots and unstructured environments as they are inherently compliant and flexible. However, this soft characteristic also leads to the challenge of feedback on contraction length and force. This study proposes an embedded proprioceptive displacement and force sensing method for tube-fiber pneumatic artificial muscle. In these actuators, the generated movement and force are due to the defamation of the tubes. The proposed sensing methods filled the tube with magnetic material, to convert the deformation of the tube into changes in the magnetic field. These changes in the magnetic field are detected by Hall sensors. Experimental results show that the output of the Hall sensor exhibits a monotonic relationship with the actual displacement and force changes, demonstrating high repeatability and low hysteresis. These findings are consistent with the behavior expected from the mathematical model. Data-driven models were built for displacement and force estimation. The accuracy was 2.87% root-mean-square error (RMSE) in measuring displacement and 4.56% RMSE in measuring force. In addition, the practical application of the sensing method is demonstrated by a human-subject test, showcasing its ability to estimate displacement and force in dynamic and practical scenarios. The integration of compact sensors within artificial muscles renders this sensing technique a promising solution for addressing the challenges of force and displacement sensing in soft artificial muscles. It offers a solution for artificial muscles and holds promise for future advancements in this field.