Incorporating Feature Signal Transmission with Block-Based Haptic Data Reduction for Time-Delayed Teleoperation

This paper presents an innovative feature signal transmission approach incorporating 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 information 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 transmission block. This methodology enables the transmission of more useful information without introducing additional delay, aside from the inherent algorithmic delay. Experimental results demonstrate the superiority of our approach over other state-of-the-art (SOTA) methods on various assessment measures under distinct channel delays.