遠隔操作のための音響ベースの粗さセンシングと触覚フィードバック
Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence
ロボット指先の音をマイクで取得し、学習ベースで表面粗さを推定して振動アクチュエータで操作者に提示する低コストな触覚システムを提案し、XPRIZE決勝で有効性を示した。
著者: Bastian Pätzold, Andre Rochow, Michael Schreiber, Raphael Memmesheimer, Christian Lenz, Max Schwarz, Sven Behnke
分類: cs.RO
原文アブストラクト
Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering system, which is capable of detecting and displaying surface roughness. As the robot fingertip moves across a surface of interest, two microphones capture sound coupled directly through the fingertip and through the air, respectively. A learning-based detector system analyzes the data in real time and gives roughness estimates with both high temporal resolution and low latency. Finally, an audio-based vibrational actuator displays the result to the human operator. We demonstrate the effectiveness of our system through lab experiments and our winning entry in the ANA Avatar XPRIZE competition finals, where briefly trained judges solved a roughness-based selection task even without additional vision feedback. We publish our dataset used for training and evaluation together with our trained models to enable reproducibility of results.
