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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.19958 |
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| _version_ | 1866910061339607040 |
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| author | Štironja, Vlaho-Josip Petrović, Luka Peršić, Juraj Marković, Ivan Petrović, Ivan |
| author_facet | Štironja, Vlaho-Josip Petrović, Luka Peršić, Juraj Marković, Ivan Petrović, Ivan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_19958 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Radar-Inertial Odometry with Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling Štironja, Vlaho-Josip Petrović, Luka Peršić, Juraj Marković, Ivan Petrović, Ivan Robotics 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. |
| title | Radar-Inertial Odometry with Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.19958 |