Banat

Banat

Banat University / ROMANIA

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Beteigeuze

Beteigeuze

Karlsruhe Institute of Technology / GERMANY

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Bullseye

Bullseye

Wageningen University / NETHERLANDS

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Cornstar

Cornstar

University of Maribor / SLOVENIA

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DTUni-Corn

DTUni-Corn

Technical University of Denmark / DENMARK

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Eduro

Eduro

Czech University of Life Sciences / CZECH REPUBLIC

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FireAnt

FireAnt

Czech University of Life Sciences / CZECH REPUBLIC

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Florence

Florence

Harper Adams University / UNITED KINGDOM

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Floribot

Floribot

Heilbronn University / GERMANY

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Fontynator

Fontynator

Fontys Venlo / NETHERLANDS

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GroundBreaker

GroundBreaker

Aalto Uni. & Uni. of Helsinki / FINLAND

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Helios

Helios

TU Braunschweig / GERMANY

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MEC

MEC

TU Kaiserslautern / GERMANY

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Pars

Pars

Gaziosmanpaşa University / TURKEY

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Smarttrike

Smarttrike

Wageningen University / NETHERLANDS

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Thalos

Thalos

University Hohenheim / GERMANY

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The Great Cornholio

The Great Cornholio

Uni. of Applied Science Osnabrueck / GERMANY

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Zephyr

Zephyr

University of Siegen / GERMANY

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General information

Team name:

Bullseye

Institution: Wageningen University
Department: Farm Technology Group
Contact: Jan Willem Hofstee

Team details

Mentors: Joris Ijsselmuiden, Sam Blaauw
Members: Rick Stegeman, Adrie Meeuwesen, Thijs Ruigrok, Sander Bouwknegt

Robot – basic information

Web page: Www.robatic.nl

Dimensions:

(W × L × H)

50x95x105 cm
Weight: 35 kg
Num. of wheels: 4 Turning radius: 15 cm
Rain resistance: Splash proof    

Robot – mechanical details

Drive concept: Direct drive
Steering: 4 wheeled ackermann
Special characteristics:  

Robot – electrical details

Powered by: ZIPPY Flightmax 8000 mAh 6S1P 30c
Motors: Maxon brushless motors
Controller: Motion Mind rev. 2
Sensors: Camera: 3x Microsoft LifeCam HD-3000 Compass: Xsens mti-30
Ultrasonic: - Gyroscope: Xsens mti-30
Infrared: - Accelerometer: Xsens mti-30
Laser: Sick LMS111 Mechanical: Kverneland potentiometer
Other: Arduino Uno
Communicatio: WiFi, bluetooth

Robot – Software

Operating system: Ubuntu 14.04 with Ros Indigo
Programmed in: Python
Tools:  
Other:  

Robot – Strategy

1st task: Using the cameras and laserscanner information, rows are detected. This information will be converted using sensor fusion and PID controllers to motorcontroller commands.
2nd task: Same as task 1, but now with additional info of which rows to drive in.
3rd task: Probably using gmapping, otherwise using odometry and xsens combinated with the information from the cameras
Free style: Detect a parking place and park the robot with trailer backwards in that spot.

Robot – Investment

Work hours: 260 hours per person, thus 1040 totally
Components: 3 cameras, motherboard and processor, Arduino Uno, potentiometer
Other:  
Sponsored by: Claas Stiftung, Wageningen University, Agrifac, Probotiq, Dacom

Problems / Challenges

Previously the robot was controlled using LabView. It was a challenge to rewrite the whole software into ROS without any prior knowledge in ROS.

Other