Sensing in Everting Vine Robots

Abstract

Acoustic signals can be used to detect environmental interactions of everting tube robots.The experiments in this thesis distinguish differences in pressure and audio signals in tubes freely everting through different-sized tunnels, with acoustic signal measurement ranging from 0-10 kHz. Pressure rises when transitioning to smaller tunnels and drops when transitioning to larger tunnels. Audio becomes louder when transitioning to larger tunnels and quieter when transitioning to smaller tunnels. Audio FFTs and spectrograms also show distinguishable eversion sounds and clear evidence of tunnel transitions. Time data suggests that reliable time series models could be created to detect tunnel transitions. Frequency data also suggests that a reliable spectral analysis model could be created to detect tunnel transitions. In practice, these findings could be used to deploy everting tubes as sensors in hard-to-reach places. In medical environments that are not easily seen and are not safe for rigid probes, such as the mammary glands, brain ventricles, the trachea and the colon, acoustic sensing can help indicate what the environment looks like and if the tube is maneuvering properly.