Olfactory Inertial Odometry: Methodology for Effective Robot Navigation by Scent

TL;DR

This paper introduces olfactory inertial odometry (OIO), a novel framework for robot navigation using scent, inspired by visual inertial odometry, demonstrated on a robot arm in real-world odor-tracking scenarios.

Contribution

It proposes a new olfactory navigation framework (OIO) that adapts principles from SLAM and VIO for scent-based robot navigation, validated with real robot experiments.

Findings

Successful demonstration of OIO on a 5-DoF robot arm.

Effective odor localization algorithms for real-world scenarios.

Baseline framework established for future olfactory navigation research.

Abstract

Olfactory navigation is one of the most primitive mechanisms of exploration used by organisms. Navigation by machine olfaction (artificial smell) is a very difficult task to both simulate and solve. With this work, we define olfactory inertial odometry (OIO), a framework for using inertial kinematics, and fast-sampling olfaction sensors to enable navigation by scent analogous to visual inertial odometry (VIO). We establish how principles from SLAM and VIO can be extrapolated to olfaction to enable real-world robotic tasks. We demonstrate OIO with three different odour localization algorithms on a real 5-DoF robot arm over an odour-tracking scenario that resembles real applications in agriculture and food quality control. Our results indicate success in establishing a baseline framework for OIO from which other research in olfactory navigation can build, and we note performance enhancements that can be made to address more complex tasks in the future.