ViT-PQC: Vision Transformer-Based Patch Quality Controller for Edge-Assisted Visual-SLAM

Edge-based visual simultaneous localization and mapping (Visual-SLAM) enables real-time indoor localization of robots by using substantial computing resources of an edge server. However, this system can place a burden on resource-constrained wireless networks because robots transmit their video data to the edge server via wireless networks. Given the sharing of the limited network capacity among multiple devices, the video bitrate needs to be reduced so as not to overshoot the available bandwidth. Although lowering the video quality can reduce the video bitrate, it also results in a loss of detailed image features and can negatively impact localization accuracy. In this paper, we propose a Vision Transformer-based patch quality controller (ViT-PQC) that reduces the video bitrate below the available bandwidth while preserving localization accuracy. ViT-PQC segments the video frame into patches and assigns an optimal image quality to each patch by taking into account both the image features of the recent frame and time shift features between the two most recent frames. Evaluation results demonstrate that ViT-PQC reduces the number of bitrate overshoots by 94% while preserving localization accuracy.