Disentangling Contact Location for Stretchable Tactile Sensors from Soft Waveguide Ultrasonic Scatter Signals - Zhiheng Li; Yuan Lin; Peter B. Shull; Hongliang Ren (Advanced Intelligent Systems)
Flexible tactile sensors have the ability to provide unparalleled levels of tactile sensation, including information regarding roughness, contact force, and contact location. However, it remains a challenge to achieve precise contact location sensing that is decoupled from sensor strain and touching forces. This paper proposes a novel data‐driven approach for force contact location sensing (FCLS) with the influence of sensor strain and forces based on scatter signals (SS) of the ultrasonic waveguide. First, the envelope of the force contact scatter signal (FCSS) is extracted via the Hilbert transform, which retrieves the global features of SS. The time‐frequency spectrogram is obtained via continuous wavelet transform, which extracts the local features of SS. Second, a deep convolutional neural network (CNN) is utilized to extract these features separately and concentrate them together. Third, based on the outputs of the CNN, a multilayer perception regression model is applied to acquire the force contact location. The experimental results indicate that the accuracy of the proposed FCLS method has a mean absolute error of 0.627 mm and a mean relative error of 3.19%. This research provides a foundation for further multimodal sensing using ultrasonic waveguides and its application in robotic sensing.