Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909638924959744 |
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| author | France, Kordel K. Daescu, Ovidiu Paul, Anirban Prasad, Shalini |
| author_facet | France, Kordel K. Daescu, Ovidiu Paul, Anirban Prasad, Shalini |
| contents | Visual inertial odometry (VIO) is a process for fusing visual and kinematic data to understand a machine's state in a navigation task. Olfactory inertial odometry (OIO) is an analog to VIO that fuses signals from gas sensors with inertial data to help a robot navigate by scent. Gas dynamics and environmental factors introduce disturbances into olfactory navigation tasks that can make OIO difficult to facilitate. With our work here, we define a process for calibrating a robot for OIO that generalizes to several olfaction sensor types. Our focus is specifically on calibrating OIO for centimeter-level accuracy in localizing an odor source on a slow-moving robot platform to demonstrate use cases in robotic surgery and touchless security screening. We demonstrate our process for OIO calibration on a real robotic arm and show how this calibration improves performance over a cold-start olfactory navigation task. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_04539 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation France, Kordel K. Daescu, Ovidiu Paul, Anirban Prasad, Shalini Robotics Emerging Technologies Machine Learning Systems and Control Visual inertial odometry (VIO) is a process for fusing visual and kinematic data to understand a machine's state in a navigation task. Olfactory inertial odometry (OIO) is an analog to VIO that fuses signals from gas sensors with inertial data to help a robot navigate by scent. Gas dynamics and environmental factors introduce disturbances into olfactory navigation tasks that can make OIO difficult to facilitate. With our work here, we define a process for calibrating a robot for OIO that generalizes to several olfaction sensor types. Our focus is specifically on calibrating OIO for centimeter-level accuracy in localizing an odor source on a slow-moving robot platform to demonstrate use cases in robotic surgery and touchless security screening. We demonstrate our process for OIO calibration on a real robotic arm and show how this calibration improves performance over a cold-start olfactory navigation task. |
| title | Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation |
| topic | Robotics Emerging Technologies Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2506.04539 |