Odor Tracking with an Electronic Nose Creating a robot that smells good! By Simon Saugier Ninh Dang Greg Allbee Jason Hamor

Problem Statement Design and implement an odor-tracking algorithm, and create a simulation environment in which to test it. Develop signal-processing procedures to reconstruct the changes in concentration of odor mixtures through the response of a gas sensor array.

Design Objective Create three simulation modules –E-nose module –Diffusion module –Robot Simulator Replace E-nose module with provided dilution system to test with real sensor responses.

Dispersion Model Three choices –Eulerian –Lagrangian –Gaussian

Eulerian & Lagrangian EulerianLagrangian

Eulerian Equation

Lagrangian Equation

Gaussian

LabVIEW Interface CIN modules Interface with C as a.dll

LabVIEW Problems Imprecise documentation Learning curve

LabVIEW Next Steps Work with other members to implement modules Integrate modules together for cohesive system

Existing Tracking Algorithms Random walk of bacteria Male moth track a female Moth pheromone plume Robot movement based on gradient The spiral surge algorithm

Final Tracking Algorithm Simple to implement and should yield good results in practice Surge spiral-like behavior Will code the model in the next several weeks while continuing searching more tracking algorithms

E-nose Simulator General: Specific: Methane –R= sensor resistance –

Dilution System Important components –Sensor responses –LabVIEW interface program Input to system –Dilution profile Output from system –Sensor responses: 4 odor, 1 temp/humidity

E-nose Problem and Next Steps Problem –Time and complexity limit number of odor sources Next –Coding of E-nose simulator –Begin pattern recognition with dilution system

Gantt Chart