Olfactory Inertial Odometry: Sensor Calibration and Drift Compensation

TL;DR

This paper introduces a calibration process for olfactory inertial odometry (OIO) that enhances odor source localization accuracy on robots, addressing sensor and environmental disturbances in scent-based navigation.

Contribution

We develop a generalized calibration method for OIO applicable to various gas sensors, improving localization accuracy in real-world robotic applications.

Findings

Calibration improves odor source localization accuracy.

The process generalizes across different olfaction sensors.

Experimental results show enhanced performance over cold-start navigation.

Abstract

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.