# 通过连续时间 IMU 建模实现在线时空标定的雷达-惯性里程计

> 原文链接：https://robotics.hellobike.com/papers/2026-10-09-2603-19958
> 频道：papers | 更新日期：2026-10-09 | 标签：arxiv, cs.RO
> 核心摘要：针对RIO常假设已知外参且忽略时间错位，提出基于连续时间IMU建模的因子图在线时空联合标定框架。

# 通过连续时间 IMU 建模实现在线时空标定的雷达-惯性里程计

::: v-pre
> 原文链接：[Radar-Inertial Odometry With Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling](https://arxiv.org/abs/2603.19958)（arXiv 2603.19958 · 发布日期：2026-10-09）

**Radar-Inertial Odometry With Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling**

针对RIO常假设已知外参且忽略时间错位，提出基于连续时间IMU建模的因子图在线时空联合标定框架。

## 核心要点

- RIO可在低光、雾、少特征环境或恶劣天气下替代视觉和LiDAR里程计。
- 现有方法常假设雷达-IMU外参已知，或依赖充分运动激励进行在线外参估计。
- 该框架在因子图优化中联合在线估计空间外参和传感器时间偏移。
- 用均匀三次B样条连续时间建模加速度和角速度，以刻画异步测量并实现参数可靠收敛。

## 英文摘要 (Abstract)

Radar-Inertial Odometry (RIO) has emerged as a robust alternative to vision- and LiDAR-based odometry in challenging conditions such as low light, fog, featureless environments, or in adverse weather. However, many existing RIO approaches assume known radar-IMU extrinsic calibration or rely on sufficient motion excitation for online extrinsic estimation, while temporal misalignment between sensors is often neglected or treated independently. In this work, we present a RIO framework that performs joint online spatial and temporal calibration within a factor-graph optimization formulation, based on continuous-time modeling of inertial measurements using uniform cubic B-splines. The proposed continuous-time representation of acceleration and angular velocity accurately captures the asynchronous nature of radar-IMU measurements, enabling reliable convergence of both the temporal offset and extrinsic calibration parameters, without relying on scan matching, target tracking, or environment-specific assumptions.

作者：Vlaho-Josip Štironja, Luka Petrović, Juraj Peršić, Ivan Marković, Ivan Petrović
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## 原始参考来源 (Sources)

- [arXiv 2603.19958：Radar-Inertial Odometry With Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling](https://arxiv.org/abs/2603.19958)