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In this work, we present two embedded soft optical waveguide sensors designed for real-time onboard configuration sensing in soft actuators for robotic locomotion. Extending the contributions of our collaborators who employed external camera systems to monitor the gaits of twisted-beam structures, we strategically integrate our OptiGap sensor system into these structures to monitor their dynamic behavior. The system is validated through machine learning models that correlate sensor data with camera-based motion tracking, achieving high accuracy in predicting forward or reverse gaits and validating its capability for real-time sensing. Our second sensor, consisting of a square cross-section fiber pre-twisted to 360 degrees, is designed to detect the chirality of reconfigurable twisted beams. Experimental results confirm the sensor’s effectiveness in capturing variations in light transmittance corresponding to twist angle, serving as a reliable chirality sensor. The successful integration of these sensors not only improves the adaptability of soft robotic systems but also opens avenues for advanced control algorithms.