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Institute of Agricultural Maschinery and Fluid Power

Precise relative positioning in machine swarms

Dipl.-Ing. Jan Schattenberg Prof. Dr.-Ing. T. Lang Dipl.-Ing. M. Becker

Dipl.-Ing. S. Batzdorfer Dr.-Ing. U. Bestmann Prof. Dr.-Ing. P. Hecker

Dr.-Ing. F. Andert

3rd International Conference on Machine Control Guidance

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 2

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 3

Urban and alpine scenario Shadowing of GNSS signals, degrading

GNSS signals, multipath effects Guidance with the help of known

landmarks is limited Fast search with high

accuracy positioning

Integration of IMU/GNSS including Failure Detection and Exclusion MethodsVision-aided relative localizationSwarm Positioning using GNSS raw data exchangeMobile Ad-hoc communication for GNSS raw data exchange

Motivation

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 4

Introduction – “NExt UAV”

Joint research project “NExt UAV“

Institute of Flight Guidance

Institute of Agricultural Machinery and Fluid Power

Institute of Flight Systems

Funded by

FKZ 50NA1002 and 50NA1003

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 5

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 6

IMU/GNSS and Vision integration - FDE

System architecture

Main filter processes all measurements (N) Each subfilter processes (N-i) measurements (i = 1…N-1)

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 7

IMU/GNSS and Vision integration – Vision based localization

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 8

IMU/GNSS and Vision integration - Coupling

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Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 9

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 10

Swarm Positioning - Standalone

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Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 11

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Swarm Positioning – Double Differential

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 12

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Swarm Positioning – Standalone & Double Differential

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 13

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 14

Mobile Ad-Hoc communication - Requirements

Quick and safe data exchange Flexible for dynamic changes in network topology Decentralized system to compensate

loss of swarm participants

MANet or Mesh networks

Without direct data linkDirect data linkMulti-hop data link

Scenarios:All2All, All2One, One2All

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 15

Mobile Ad-Hoc communication - Simulation

Using MATLAB® Proactive routing – All2All 4 to 12 nodes 1000 simulations Steps:

1. Generate random network2. Network discovery3. Routing4. Data Exchange

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 16

Mobile Ad-Hoc communication - Implementation

Network exploration Calculating the routing table GNSS raw data exchange Data processing

Network Exploration GNSS raw data exchange

1 Hz update frequency syncronized by PPS

100msCalculating

Routing Table

Data processing

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 17

Mobile Ad-Hoc communication – Network Exploration

Problem: No a-priori knowledge and no coordinator Try and Error Tools: Clear Channel Assessment (CCA)

Scan energy level of channel Compare detected energy with threshold If medium not clear wait random backoff time and try again

Problems: Hidden stations

No ACK available using broadcast messages

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 18

Mobile Ad-Hoc communication – Network Exploration

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 19

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 20

First Results – Reference systems

Reference localization system (Leica Viva TS15 ) tracking with up to 6 Hz compare track with GNSS/INS solution Sync by GNSS-time using WLAN and NTP

Phase solution in post-processing

UAV 1

UAV 2

UAV 3

Ref-Station

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 21

First Results - Measurements

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 22

Motivation and Introduction

IMU/GNSS and Vision integration

Swarm Positioning

Mobile Ad-Hoc Communication

First Results

Conclusion and Outlook

Outline

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 23

Conclusion and Outlook

Absolute and relative position is indispensable Positioning techniques and controlling strategies require

swarm communication Algorithm for network exploration fits simulation results

Test of all sub-systems together in one system Tests in different scenarios (urban, alpine, different constellations) Optimization of the required time minimization of the required

messages

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 24

Thank you for your attention!

comRoBS

Dipl.-Ing. Jan SchattenbergJ.Schattenberg@tu-braunschweig.deTel.: +49 (0) 531 391-7192Fax: +49 (0) 531 391-5951

www.tu-braunschweig.de/ilfilf@tu-braunschweig.de

Institute of Agricultural Machinery and Fluid Power

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 25

2x dual axis MEMS acceleration sensor (Bosch SMB225)

3x 1-axis gyro sensor (Bosch SMG074 )

1x “read-out”-board layout and design by IFF

NExt UAV - IMU

µblox LEA-6T-chip (Precision Timing & Raw Data)Hybrid GPS/SBAS engine (WAAS, EGNOS, MSAS)Basis-Board layout and design by messWERK

NExt UAV - GNSS

Technical Equipment

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 26

• Seco Qseven™ Embedded Computer Module• Pico ITX-Standard (3,9”x2,0”, 100 x 72 mm)• Intel Atom (Z530) 1,6 GHz, 1 GB DDR2, 800 Hz bus• 8 GB Flashdrive, microSD-Slot (8 GB), SD-Slot (8

GB)• Operating system: linux with real time extension

NExt UAV- NAV-Board

• Wireless standard 802.15.4 XBee• Frequency Band 2,4 GHz ISM• Radio range up to 1.6 km• Serial Data Range up to 115.2 Kbps

NExt UAV- Radio module

Technical Equipment

Institute of Agricultural Machinery and Fluid Power29.03.2012 | Dipl.-Ing. Jan Schattenberg | Precise relative positioning in machine swarms | Slide 27

• 2x AlliedVisionTec Marlin F-131B with Pentax C815B • Self-made carrier for stereo camera system• Interface: IEEE 1394a - 400 Mb/s• Resolution: 1280 x 1024• 25 fps on full resolution

NExt UAV- Vision

Technical Equipment

• Lippert CXR-GS45 PCI104Ex with Core2Duo 9300• 2 GB Ram• Firewire expansion board

NExt UAV- Vision-Board