1. We thank the Office of Research and Sponsored Programs for supporting this research, and Learning & Technology Services for printing this poster.
INTEGRATION OF ATMOSPHERIC SENSORS
INTO UNMANNED AERIAL VEHICLE
PLATFORMS
Matthew Kennedy1, Patricia Cleary2, Peter Bui1, Joe Hupy3
1. Department of Computer Science, UW-Eau Claire 2. Department of Chemistry, UW-Eau Claire 3. Department of Geography and Anthropology, UW-Eau Claire
Applications of Unmanned Aerial Vehicles (UAVs) are being
investigated at University of Wisconsin-Eau Claire as part of a
Geospatial Education Initiative. The development of a UAV
capable of monitoring atmospheric properties (temperature,
humidity and wind) and composition (ozone) is underway. The
integration of temperature, humidity, and ozone sensors onto a
fixed wing UAV poses several problems with respect to electrical
power, weight, data acquisition and data storage. One strategy
requires the implementation of a central micro-controller for
onboard data acquisition and storage. The goal for full integration
of sensor control and data acquisition is for real-time data output
through the on-board auto-pilot feature so that the UAV flight
can be adjusted for observed atmospheric conditions. The
development of the auto-pilot/telemetry feature will also be
discussed.
Image 1 - RV Jet on trial flight with Personal Ozone Monitor in payload. Result : Crash
ABSTRACT
USING ADDITIONAL EQUIPMENT TO SEND SENSOR DATA
One of the end goals is to receive our external sensor data in real-time. This
is possible, as the autopilot already uses several external sensors to
determine its position, speed, etc. In the software exists an exploit that
should allow us to send sensor data in real-time by simply changing a few
select lines in the source code. We will utilize a structure already put in place
that would normally relay sonar data. Since we are not using sonar for this
project, it lends itself perfectly to this application.
INTEGRATION SOLUTIONS
• HMP-60 for temperature/humidity
• 5-hole probe for wind velocity
• Ozone sensor
In addition to the authors of this poster were co-collaborators working
on all other aspects of this project. Max Lee, Physics, made all telemetry
systems and oversaw the building of multiple UAVs. Joe Oster,
Chemistry, takes the data retrieved from the sensor packages and uses
that data to answer questions related to atmospheric environments
that he is studying.
PROJECT OBJECTIVES
Image 2 - RV Jet with radio transmitter and ground station
ENGINEERING CHALLENGES
USING EXISTING EQUIPMENT TO SEND SENSOR DATA
The first approach used to analyze data was to use an Arduino micro-
controller to gather sensor data and store it onto an SD card. This is a very
effective method for logging data, but for real-time analysis it is weak. In
addition a method utilizing GSM communication was hypothesized for near
real-time data transmission.
ACKNOWLEDGMENTS
INTEGRATE SENSORS INTO UAS
GATHER DATA IN A DYNAMIC ENVIRONMENT
Traditionally, atmospheric data has been gathered in a static
environment such as a weather station . Integrating similar
sensors into a UAV will allow a much more dynamic view of
atmospheric activity.
GATHER DATA IN A REAL TIME
Post-processed data can be useful for testing certain hypothesis,
but to allow for on-the-fly flight path changes, real-time data must
be transmitted. This will allow for instant recognition of
anomalous zones.
Gathering data is easy. Engineering a system to communicate that data
in an efficient way, especially in real-time, is not. A lack of similar
projects to reference also made things more complicated. When trying
to integrate into a finely tuned system like a UAV, you must be careful
not to have any kind of interference, especially with parts directly
responsible for flight and navigation.
FUTURE CHALLENGES
• Configured hardware to read sensor data
• Wrote software to send serial data to logger
• Fit hardware into already full payload.
• Increased precision by adding external ADC.
• Rewrite module to show data in Mission Planner
• Integrating ozone sensor more fully
• Write software to easily combine multiple data logs.
• Write additional module to show real-time data for multiple
sensors.
PROJECT MILESTONES
CURRENT HURDLES
• Compiler issues - Since source code needs to be changed,
firmware must be compiled and flashed to the autopilot
• Large learning curve to software already written.
• Extremely interdisciplinary experiment, which requires a
specially-designed, novel solution, so there is no “manual”