This paper presents an innovative feature signal transmission approach incorpo-rating block-based haptic data reduction to address time-delayed teleoperation. Numerous data reduction techniques rely on perceptual deadband (DB). In the preceding block-based approaches, the whole block within the DB is discarded. However, disregarding all signals within the DB loses too much information and hinders effective haptic signal tracking, as these signals contain valuable infor-mation for signal reconstruction. Consequently, we propose a feature signal transmission approach based on the block algorithm that aggregates samples as a unit, enabling high-quality haptic data reduction. In our proposed approach, we employ max-pooling to extract feature signals from the signals within the DB. These feature signals are then transmitted by adjusting the content of the trans-mission block. This methodology enables the transmission of more useful infor-mation without introducing additional delay, aside from the inherent algorithmic delay. Experimental results demonstrate the superiority of our approach over oth-er state-of-the-art (SOTA) methods on various assessment measures under dis-tinct channel delays.

翻译：本文提出了一种创新的特征信号传输方法，结合基于块的触觉数据缩减技术，以应对时延遥操作问题。许多数据缩减技术依赖于感知死区。在以往的基于块的方法中，死区内的整个块会被丢弃。然而，忽略死区内所有信号会丢失过多信息，并阻碍有效的触觉信号跟踪，因为这些信号包含了对信号重建有价值的信息。为此，我们提出了一种基于块算法的特征信号传输方法，该方法将样本聚合为一个单元，从而实现高质量的触觉数据缩减。在我们的方法中，采用最大池化从死区内的信号中提取特征信号，然后通过调整传输块的内容来传输这些特征信号。该方法能够在除算法固有延迟外不引入额外延迟的情况下，传输更多有用信息。实验结果表明，在不同信道延迟条件下，我们的方法在多种评估指标上均优于其他最先进方法。