Unmanned Aerial Vehicles as Mobile Multi-sensor Platforms

Matthes Rieke, Theodor Foerster, Arne Broering

Institute for Geoinformatics – University of Muenster

AGILE 2011 Conference, Utrecht, 2011-04-19

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Overview

1. Introduction

2. Sensor platforms

3. Framework Approach

4. Integration into the Sensor Web

5. Future Work and Impressions

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● Use case from landscape ecology

● Determine meteorological inversions in the Prandtl-Layer

Introduction

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● Mobile Multi-sensor Platform ● Unmanned Aerial Vehicle (UAV) as base ● Extended with several sensors

● Problems raised from this approach

● Different UAVs - different data encodings ● Varying sensors with specific low-level protocols

● How to integrate gathered data into the Sensor Web?

Introduction

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● Quick answer

● Abstract the integration layer from protocol specifics

● Framework Approach – described later on

Introduction

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Overview

1. Introduction

2. Sensor platforms

3. Framework Approach

4. Integration into the Sensor Web

5. Future Work and Impressions

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● Several UAVs available in the civilian domain

● Community Projects - e.g.

● Mikrokopter ● ArduCopter

● Commercial Projects - e.g.

● Microdrone ● AscTec

Sensor platforms

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Sensor platforms

● Basis is a building kit by www.mikrokopter.de

● Wireless downlink included

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Sensor platforms

● How to measure phenomena?

● Integrate independent computing unit ● Actual sensors are operated ● Independent wireless downlink

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Sensor platforms

● System summary

● Mikrokopter UAV with downlink for GPS tracking ● Independent „Sensor Board“ for phenomena

measurement

→ Two separated data streams New problem: How to fuse streams to enable real-time data provision?

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Overview

1. Introduction

2. Sensor platforms

3. Framework Approach

4. Integration into the Sensor Web

5. Future Work and Impressions

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Framework Approach

● Requirement summary

● Support for different UAV platforms ● Synchronization of multiple data streams to enable

real-time measurement capabilities ● Sensor Web integration mechanism

● Realized using Software Framework

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Framework Approach

● Architecture

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Framework Approach

● Basis is description of Plugin Behaviour ● Input/Output phenomena using SensorML ● When to create Output?

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Framework Approach

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<?xml version="1.0" encoding="UTF-8"?> <spf:plugin xmlns:spf=http://ifgi.uni-muenster.de/~m_riek02/spf/0.1 name="urn:ifgi:id:ifgicopter2"> <spf:output> <spf:AvailabilityBehaviour> <spf:outputProperties> <spf:property>temperature</spf:property> <spf:property>humidity</spf:property> </spf:outputProperties> </spf:AvailabilityBehaviour> <spf:mandatoryProperties> <spf:property>position</spf:property> </spf:mandatoryProperties> </spf:output> <SensorML /> </spf:plugin>

Framework Approach

● Synchronization of sensor streams

● Why synchronize streams? ● Have geotagged observations in real-time

● e.g. used by Complex Event Processing

● Overcome bandwidth issues (details later)

● Use of interpolation mechanism ● Abstract – easily adjustable for application

● Additional processing capabilities

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Framework Approach

● Called once internal output is created

● Functionality only triggered by framework ● No limitations

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Reminder:

Overview

1. Introduction

2. Sensor platforms

3. Framework Approach

4. Integration into the Sensor Web

5. Future Work and Impressions

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Integration into the Sensor Web

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Integration into the Sensor Web

● achieved using Output-Plugin for the so-called Sensor Bus

• communication infrastructure which underlies the different Sensor Web services (SOS, SES, SPS, etc.)

• Well-defined communication protocol

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Integration into the Sensor Web

● Establish connection to Sensor Bus → integration

into connected SWE services

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Integration into the Sensor Web

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Test evaluations

Overview

1. Introduction

2. Sensor platforms

3. Framework Approach

4. Integration into the Sensor Web

5. Future Work and Impressions

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Future Work

● Differential GPS: Orthophotos without Ground Control Points

● Exterior Orientation ● Position (GPS)

● Rotation (IMU)

● Interior Orientation ● Principal point and distance

(Camera calibration file)

● Terrain Model

● → Orthophoto

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Future Work

● Visualization ● Additional sensors

● Fine dust ● Gas sensors

● Digital elevation models ● Autonomic flight (security and surveillance)

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Source Code available at:

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Thank you for your kind attention! Questions?

http://purl.net/ifgi/copter → UAV Workshop @ Geoinformatik 2011

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