LLOL: Low-Latency Odometry for Spinning Lidars
This addresses latency issues for real-time robotics and autonomous systems, though it is incremental as it builds on existing lidar odometry methods.
The paper tackles the problem of high latency in lidar odometry by processing data from spinning lidars as a stream instead of waiting for full sweeps, resulting in a fast and lightweight system with higher throughput and lower latency.
In this paper, we present a low-latency odometry system designed for spinning lidars. Many existing lidar odometry methods wait for an entire sweep from the lidar before processing the data. This introduces a large delay between the first laser firing and its pose estimate. To reduce this latency, we treat the spinning lidar as a streaming sensor and process packets as they arrive. This effectively distributes expensive operations across time, resulting in a very fast and lightweight system with much higher throughput and lower latency. Our open-source implementation is available at \url{https://github.com/versatran01/llol}.