Audio-Based Tactile Human-Robot Interaction Recognition

• URL: http://arxiv.org/abs/2512.11873v1
• Date: Sat, 06 Dec 2025 23:19:22 GMT
• Title: Audio-Based Tactile Human-Robot Interaction Recognition
• Abstract summary: This study explores the use of microphones placed on a robot's body to detect tactile interactions via sounds produced when the hard shell of the robot is touched.<n>Two I2S microphones integrated with a Raspberry Pi 4 were positioned on the torso of a Pollen Robotics Reachy robot to capture audio signals.<n>A convolutional neural network was trained for touch classification on a dataset of 336 pre-processed samples.<n>The model shows high classification accuracy between touch types with distinct acoustic dominant frequencies.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study explores the use of microphones placed on a robot's body to detect tactile interactions via sounds produced when the hard shell of the robot is touched. This approach is proposed as an alternative to traditional methods using joint torque sensors or 6-axis force/torque sensors. Two Adafruit I2S MEMS microphones integrated with a Raspberry Pi 4 were positioned on the torso of a Pollen Robotics Reachy robot to capture audio signals from various touch types on the robot arms (tapping, knocking, rubbing, stroking, scratching, and pressing). A convolutional neural network was trained for touch classification on a dataset of 336 pre-processed samples (48 samples per touch type). The model shows high classification accuracy between touch types with distinct acoustic dominant frequencies.

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