LLOL: Low-Latency Odometry for Spinning Lidars

Chao Qu, Shreyas S. Shivakumar, Wenxin Liu, Camillo J. Taylor

2022 International Conference on Robotics and Automation (ICRA) · 2022 · 18 citations · 28 references

Concepts

Abstract

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 a much higher throughput and lower latency. Our open source implementation is available at https://github.com/versatran01/llol.

References

28