Low Latency Transmission of Filtered LiDAR Point Cloud Data over RF (Radio Frequency) Channels: Enhancing Efficiency for Real-Time Applications

Abstract

This study presents a novel approach to enhancing teleoperation systems by integrating LiDAR point cloud data as a supplementary tool alongside traditional video streaming. Recognizing the limitations imposed by video transmission's heavy data requirements and latency issues, our research focuses on utilizing LiDAR technology not as a replacement but as a tactical supplement to camera systems. By applying algorithms that filter and transmit only essential points of the objects within specified degrees and distances, we aim to significantly reduce the data load. This method allows for the transmission of critical spatial information via RF (Radio Frequency) modems with a bandwidth as limited as 500kbps, typical of telemetry systems used in drones. The core of our investigation examines how heavily filtered LiDAR point cloud data can be effectively transmitted over these low-bandwidth channels, offering a potential breakthrough in remote sensing and communication for teleoperated applications. While acknowledging the utility of high-throughput RF modems that could, in certain scenarios, enable a reliance solely on LiDAR data, our research is particularly focused on optimizing data transmission within stringent bandwidth constraints. This approach promises substantial improvements in real-time data transmission efficiency and accuracy, addressing critical latency challenges in teleoperation and potentially transforming how robotic systems are remotely controlled and interacted with.