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.

翻译：触觉感知对于机器人的沉浸式远程操作至关重要，尤其是完成操作任务时。我们提出了一种低成本触觉感知与渲染系统，能够检测并显示表面粗糙度。当机器人指尖在感兴趣表面上移动时，两个麦克风分别捕捉直接通过指尖传导的声音和通过空气传播的声音。一个基于学习的检测器系统实时分析数据，并以高时间分辨率和低延迟提供粗糙度估计。最后，基于音频的振动执行器将结果呈现给人类操作员。我们通过实验室实验以及在ANA Avatar XPRIZE竞赛决赛中的获胜表现验证了系统的有效性——在该决赛中，经过短期培训的评委即使在缺乏视觉反馈的情况下，也能解决基于粗糙度的选择任务。我们公开发布用于训练和评估的数据集以及训练好的模型，以确保结果的可复现性。