LLOL: Low-Latency Odometry for Spinning Lidars

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

ICRA 2022poster24 citations

LLOL: Low-Latency Odometry for Spinning Lidars

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

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.

BibTeX

@inproceedings{icra2022_llollowlatencyod,
  title = {LLOL: Low-Latency Odometry for Spinning Lidars},
  author = {Chao Qu and Shreyas S. Shivakumar and Wenxin Liu and Camillo J. Taylor},
  booktitle = {ICRA 2022},
  year = {2022}
}