unmanned aerial vehicles as Òdata mulesÓ for ... · Òdata mulesÓ for reconnaissance and...

Unmanned Aerial Vehicles as “Data Mules” for Reconnaissance and Environmental Monitoring

- Srikanth Saripallihttp://robotics.asu.edu

srikanth.saripalli@asu.edu

ARIZONA STATE UNIVERSITY / SCHOOL OF EARTH AND SPACE EXPLORATION

Wednesday, June 12, 13

Data Mules• An Unmanned Aerial Vehicle (UAV) that has

• wireless communication capability • sufficient amount of storage to store the data from the sensors in the field.

• Travels across the sensing field and collects data from each sensor node and later deposits all the data to the base station.

• Improve servicing strategies (time, $$$, safety)• Telemetry: State of Health; data samples• Robotic data retrieval• Feasible for broad range of conditions (environmental; across political boundaries)

• Data mule flies to remote site based on flight plan or autonomous navigation• Can be tasked to “loiter” at specific waypoints• Design is to fly to site, make contact with ground• recording system, loiter during WiFi data transfer• Can also gather images and other relevant data

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• First Cut - 400 gm UAV• Includes autopilot, GPS, camera• 40 mph flight speed• 1.5 kg payload capacity• $1,000 per vehicle

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Drawbacks of Low-Cost UAV Exploration in Field Tests• Power Restrictions

• Batteries - limited flying time ~20 min• Fuel - more expensive UAVs which require advanced pilots and frequent repairs• Remote deployments make refueling/charging difficult in the field

• Wind/Weather Conditions• Most small-scale UAVs are difficult to operate in winds exceeding 15m/s• Inclement weather requires canceling tests

• Restricted Take-Off / Landing Locations• Heavy vegetation or rough terrain can make landing UAVs very difficult.

• Reliability / Repairability• Low-cost UAVs are often cheaply constructed and are prone to wear & tear,

and require constant repairs and attention• Other Concerns

• Waypoint following inaccuracies• Payload carrying capacity

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UAV COMPARISON

Udrones Arduplane-AP-X• Cost: $550 USD• Autopilot: APM 2.5• Carrying Capacity: 300g• Time: ~20min• Wind Tolerance: <15m/s

Fixed-Wing QuadRotor Helicopter Kite Plane

MikroKopter Quadro XL • Cost: $1600 USD• Autopilot: FlightCtrlME• Carrying Capacity: 2.5kg• Time: ~20min• Wind Tolerance: <10m/s

Rotomotion SR30• Cost: ~$15000 USD• Autopilot: Proprietary• Carrying Capacity: 8kg• Time: ~90min• Wind Tolerance: <20m/s

AUTOKITE• Cost: < $1000 USD• Autopilot: APM 2.5• Carrying Capacity: 1kg• Time: 50min + soaring• Wind Tolerance: <15m/s

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COST V. PILOT EXPERIENCEWednesday, June 12, 13

WIND SPEED V. FLIGHT TIMEWednesday, June 12, 13

REPAIR COST V. RELIABILITYWednesday, June 12, 13

SYSTEM DESIGN

Aircraft Specifications• Dimensions - 2.4 x 0.8 x 0.8 m• Weight - 2kg• Carrying Capacity - 1.3kg• Wing Area - 1m² • Wing Type - Delta• Wind Tolerance - <15 m/s• Avg. Speed - 6m/s• Range > 10km• Altitude - 500m

System Flow

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SYSTEM DESIGN

Systems Specifications• 12V Brushless Motor,1400 RPM

w/ 10x4.7 Slow Flier Prop• 12V Servos: Center of Gravity,

Rudder, and Camera Tilt• ArduPilot Mega 2.5 Controller• 3000 mAh LiPoly 2C discharge• 2.4Ghz Radio RX/TX• Xbee900 - 900MHz Telemetry • Canon SX-230 GPS enabled

running CHDK intervalometer at 1Hz

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FIELD USE

[ VIDEO ]

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STRUCTURE FROM MOTION

Point cloud and stitching generate structure from motion for images taken by AUTOKITE in the field. Generated by Agisoft’s Photoscan

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ORTHOPHOTOWednesday, June 12, 13

ERRORWednesday, June 12, 13

DEMWednesday, June 12, 13

Future Goals• On-demand Processing

• UAV can be tasked in real-time by remote station

• Survey Mode - Periodic Monitoring• Regular Autonomous surveys

• Change detection• Using 3D maps obtained from UAVs

and comparing them with LIDAR data to detect 3d changes

Telica Volcano

•Actual fault caused by the earthquake shown by green lines

•Direction of the arrows•Red and white dots on either side of the fault showing height differences

Wednesday, June 12, 13