Point Cloud in the Air

摘要

Acquiring and processing point clouds (PCs) play a pivotal role in powering a variety of cutting- edge applications that rely on 3D spatial information, including robot navigation, autonomous driving, and augmented reality. These applications often require PCs, captured by remote sensors, to be wirelessly transmitted to an edge server for crucial operations such as fusion, segmentation, or inference. However, the wireless transmission of PCs introduces significant challenges due to the inherent congestion in wireless spectra and the unique complexities presented by the irregular and unstructured nature of PCs. In this article, we delve into these challenges with a detailed analysis, critically evaluating the existing methodologies and their limitations. Addressing these complexities, we introduce three innovative solution frameworks that leverage advanced techniques, hybrid strategies, and distributed data aggregation to optimize the transmission process. In doing so, our goal is to chart a path toward efficient, reliable, and low-latency wireless PC transmission.