This paper presents a novel soft tactile skin (STS) technology operating with sound waves. In this innovative approach, the sound waves generated by a speaker travel in channels embedded in a soft membrane and get modulated due to a deformation of the channel when pressed by an external force and received by a microphone at the end of the channel. The sensor leverages regression and classification methods for estimating the normal force and its contact location. Our sensor can be affixed to any robot part, e.g., end effectors or arm. We tested several regression and classifier methods to learn the relation between sound wave modulation, the applied force, and its location, respectively and picked the best-performing models for force and location predictions. Our novel tactile sensor yields 93% of the force estimation within 1.5 N tolerances for a range of 0-30+1 N and estimates contact locations with over 96% accuracy. We also demonstrated the performance of STS technology for a real-time gripping force control application.

翻译：本文提出一种基于声波的新型软体触觉皮肤（STS）技术。在该创新方法中，扬声器产生的声波沿嵌入软膜中的通道传播，当外部压力导致通道变形时声波被调制，最终由通道末端的麦克风接收。该传感器采用回归与分类方法分别估计法向力及其接触位置。我们的传感器可安装在机器人任意部件（如末端执行器或机械臂）上。我们测试了多种回归与分类器方法以学习声波调制与施加力及其位置之间的关系，并选取了性能最优的模型进行力与位置预测。该新型触觉传感器在0-30+1 N量程内，力估计误差在1.5 N容差范围内的准确率达93%，接触位置估计准确率超96%。我们还通过实时抓取力控制应用展示了STS技术的性能。