[ICRA 2025] Real-Time LiDAR Point Cloud Compression and Transmission for Resource-constrained Robots
Authors: Yuhao Cao, Yu Wang and Haoyao Chen from the Networked Robotics and Systems Lab, HITSZ Our paper is currently undergoing peer review. The code and application will be released once the paper is accepted.
We propose a real-time LiDAR point cloud compressionand transmission framework for resource-constrained robots,named RCPCC, which achieves a high compression rate,maintains high application-level accuracy, and operates at a speed (>10 Hz) that exceeds the LiDAR point cloud generation rate, enabling computationally constrained robots tooffload computation-intensive tasks to the cloud. To address bandwidth limitations and fluctuations during transmission,we propose a QoE-based adaptive bitrate control strategy thatadjusts the transmission quality based on the current and historical buffer queue lengths, ensuring optimal QoE and guaranteeing real-time and stable point cloud transmission.