Odor Tracking with An Electronic Nose May 5, 2003 Jason Hamor Greg Allbee Ninh Dang Simon Saugier.

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Presentation transcript:

Odor Tracking with An Electronic Nose May 5, 2003 Jason Hamor Greg Allbee Ninh Dang Simon Saugier

Project Background Study the response of odor sensor Research now is focused on putting E-nose on mobile robot Robot movements depend on E-nose sensing

Objectives and Deliverables To simulate an odor tracking robot in LabView To create dispersion model Integrate the robot simulator, dispersion model with the existing Dilution system

Design Model

LabView Interface Robot Control Room Control Odor Source Control Sensor Charts Simulation Picture

LabView Interface Screen Shots

LabView Diagram Screenshot

Odor Tracking Algorithm Four-Phase Algorithm: Set/Clear Variables First Step 8-point Circle Track Gradients Momentum and direction based on weighted average of history and max point.

Diffusion Model Gaussian Dispersion model Single source and Multiple sources

Diffusion Model Screenshots

E-nose Integration Testing Response of sensors Series vs. Parallel connection Optimize Gaussian model

Difficulties Encountered E-nose is not accurate E-nose is not precise Sensors heat up Sensors lag in response

Dynamic Odor Delivery System (Existing Dilution System)

Working System Graphics

System Graphics (Cont)

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