系统评估激光雷达里程计组件，给出实证设计建议
A Comprehensive Evaluation of LiDAR Odometry Techniques
- 拆解激光雷达里程计流程，逐项测试各模块性能
- 在多类数据集与场景下验证组件表现，覆盖不同设备与运动模式
- 基于实测结果推荐最优模块组合，指导未来系统设计
激光雷达（LiDAR）已成为机器人状态估计任务的首选传感器。近年来，大量研究致力于寻找最精确的激光雷达里程计（LO）方法，但多数工作仅比较整体“流水线”性能，缺乏对各核心组件的系统性消融分析。本文梳理了构成LO流水线的关键技术，并在涵盖多种环境、激光雷达类型和车辆运动模式的广泛数据集上，对这些组件进行了实证评估。最终，基于实验结果，提出可提升精度与可靠性的未来流水线设计建议。
原文摘要 · Abstract (English)
Light Detection and Ranging (LiDAR) sensors have become the sensor of choice for many robotic state estimation tasks. Because of this, in recent years there has been significant work done to fine the most accurate method to perform state estimation using these sensors. In each of these prior works, an explosion of possible technique combinations has occurred, with each work comparing LiDAR Odometry (LO) "pipelines" to prior "pipelines". Unfortunately, little work up to this point has performed the significant amount of ablation studies comparing the various building-blocks of a LO pipeline. In this work, we summarize the various techniques that go into defining a LO pipeline and empirically evaluate these LO components on an expansive number of datasets across environments, LiDAR types, and vehicle motions. Finally, we make empirically-backed recommendations for the design of future LO pipelines to provide the most accurate and reliable performance.
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