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.
@article{arxiv.2506.04539,
title = {Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation},
author = {Kordel K. France and Ovidiu Daescu and Anirban Paul and Shalini Prasad},
journal= {arXiv preprint arXiv:2506.04539},
year = {2025}
}
Comments
Published as a full conference paper at the 2025 IEEE International Symposium on Inertial Sensors & Systems