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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.00371 |
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| _version_ | 1866918041544032256 |
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| author | Gao, Yizhou Barfoot, Tim |
| author_facet | Gao, Yizhou Barfoot, Tim |
| contents | We present a new method to combine several rigidly connected but physically separated IMUs through a weighted average into a single virtual IMU (VIMU). This has the benefits of (i) reducing process noise through averaging, and (ii) allowing for tuning the location of the VIMU. The VIMU can be placed to be coincident with, for example, a camera frame or GNSS frame, thereby offering a quality-of-life improvement for users. Specifically, our VIMU removes the need to consider any lever-arm terms in the propagation model. We also present a quadratic programming method for selecting the weights to minimize the noise of the VIMU while still selecting the placement of its reference frame. We tested our method in simulation and validated it on a real dataset. The results show that our averaging technique works for IMUs with large separation and performance gain is observed in both the simulation and the real experiment compared to using only a single IMU. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_00371 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tunable Virtual IMU Frame by Weighted Averaging of Multiple Non-Collocated IMUs Gao, Yizhou Barfoot, Tim Robotics We present a new method to combine several rigidly connected but physically separated IMUs through a weighted average into a single virtual IMU (VIMU). This has the benefits of (i) reducing process noise through averaging, and (ii) allowing for tuning the location of the VIMU. The VIMU can be placed to be coincident with, for example, a camera frame or GNSS frame, thereby offering a quality-of-life improvement for users. Specifically, our VIMU removes the need to consider any lever-arm terms in the propagation model. We also present a quadratic programming method for selecting the weights to minimize the noise of the VIMU while still selecting the placement of its reference frame. We tested our method in simulation and validated it on a real dataset. The results show that our averaging technique works for IMUs with large separation and performance gain is observed in both the simulation and the real experiment compared to using only a single IMU. |
| title | Tunable Virtual IMU Frame by Weighted Averaging of Multiple Non-Collocated IMUs |
| topic | Robotics |
| url | https://arxiv.org/abs/2506.00371 |