Name
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. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICRA46639.2022.9811605 | IEEE International Conference on Robotics and Automation |
DocType | Volume | Issue |
Conference | 2022 | 1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Qu | 1 | 48 | 5.44 |
| Shreyas S. Shivakumar | 2 | 40 | 4.46 |
| Wenxin Liu | 3 | 63 | 11.65 |
| Camillo J. Taylor | 4 | 2889 | 403.50 |