Precise relative positioning in machine swarms
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Transcript of Precise relative positioning in machine swarms
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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 [email protected].: +49 (0) 531 391-7192Fax: +49 (0) 531 391-5951
www.tu-braunschweig.de/[email protected]
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