LLOL: Low-Latency Odometry for Spinning Lidars

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.

Faster-LIO: Lightweight Tightly Coupled Lidar-Inertial Odometry Using Parallel Sparse Incremental Voxels

“…For spinning lidars, there are also low-latency approaches (LoLa-SLAM [31], LLOL [32]) that do not wait for a full scan but use partial scan data to perform the registration. Such acceleration is done by slicing the scans into several patterns, and the number of registration points is also much smaller than processing a full scan.…”