Localization for Soccerrobots using Omnivision Lennart Waltke - - PowerPoint PPT Presentation

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Localization for Soccerrobots using Omnivision Lennart Waltke - - PowerPoint PPT Presentation

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MIN Faculty Department of Informatics Localization for Soccerrobots using Omnivision Lennart Waltke University of Hamburg Faculty of Mathematics, Informatics and Natural Sciences Department of Informatics Technical Aspects of Multimodal

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MIN Faculty Department of Informatics

Localization for Soccerrobots using Omnivision

Lennart Waltke

University of Hamburg Faculty of Mathematics, Informatics and Natural Sciences Department of Informatics Technical Aspects of Multimodal Systems

  • 07. Januar 2019
  • L. Waltke – Omnivision for Localization

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Outline

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

  • 1. Motivation
  • 2. Soccerrobot
  • 3. Omnidirectional Camera
  • 4. Possible Preprocessing
  • 5. Monte Carlo Method
  • 6. Field Geometry Usage

Dual-Circle Self-Localization White Line Pattern Match Pattern Match with Motion

  • 7. Conclusion
  • 8. Sources
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Motivation

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[9] Soccergame

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Navigation

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ perception ◮ localization ◮ cognition ◮ motion control

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Localization

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[8] Where Am I ?

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Localization

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ is needed for navigation of mobile robots ◮ robot must determine its position in the environment ◮ Problem: Localization is not 100% accurate

◮ sensornoise/-error ◮ effectornoise/-error

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Soccerrobot

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[9] Soccerrobot

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Omnidirectional Camera

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[7] Omnidirectional Camera

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Omnidirectional Camera

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[3] Omnidirectional Camera Scheme

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Omnidirectional Camera

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ ideal omnidirectional camera capture light from every direction ◮ in practice often only 360 degree around the equator with top

and bottom cut off

◮ if full sphere is covered, more than one focal point

[4] Image from Omnidirectional Camera

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Possible Preprocessing

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ because omnidirectional images are very distorted, it is possible

to calculate a normal (panoramic) picture

◮ also for most approaches scanlines are added

[1] Scanlines

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Monte-Carlo Self-Localization

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ using particle filter for localization ◮ each particle is estimation of robots position ◮ particles are updated over time

[2] Expected Scan

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Advantages and Disadvantages

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ Advantages:

◮ very good with many particles ◮ fast with few particles

◮ Disadvantages:

◮ high computational cost with many particles ◮ not very good with few particles [2] Many and Few Particles Used

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Dual-Circle Self-Localization

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ uses known landmarks in the environment for localization ◮ uses a hybrid scanning method

◮ Gap Scanning ◮ Polar Scanning

◮ uses two coordinate systems

◮ field coordinate system ◮ robot center coordinate system

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Simulation

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[1] Simulation for DCSL

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Experiment

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[1] Experiment for DCSL without and with Kalman Filter

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Advantages and Disadvantages

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ Advantages of Dual-Circle Self-Localization

◮ faster than Monte-Carlo Localization ◮ more precise than Monte-Carlo Localization

◮ Disadvantages of Dual-Circle Self-Localization

◮ sensitive to changes in lighting conditions

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White Line Pattern Match Localization

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ uses a grid for localization ◮ looks at the first white pixels found on scan lines ◮ uses a built-in database to compare position using nearest

distance

[4] Visualization of the Grid

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Scan Lines

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

[4] Visualization of the Scanlinevector

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Advantages and Disadvantages

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ Advantages:

◮ very fast ◮ robust to illumination changes

◮ Disadvantages:

◮ poor reliability ◮ not competetive in real competition

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Pattern Match with Motion Information

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ uses motion information to make pattern match more robust ◮ still very fast

[5] Omnidirectional Moving Base of Robot

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Conclusion

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ many different approaches for omni-vision based

self-localization

◮ has to work towards real-time ◮ trade-off between precision and computation speed ◮ Current approach: Vision System combined with Motion

System Data

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End

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

Thank You!

Any Questions ?

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Sources

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ [1] Chen-Chien Hsu, Ching-Chang Wong, Hung-Chih Teng,

Cheng-Yao Ho, "Dual-Circle Self-Localization for Soccer Robots with Omnidirectional Vision", Journal of the Chinese Institute of Engineers, Vol. 35, Issue 6, Pages619-631, 2012

◮ [2] E. Menegatti, A. Pretto, A. Scarpa, E. Pagello,

"Omnidirectional Vision Scan Matching for Robot Localization in Dynamic Environments", IEEE Transactions on Robotics,

  • Vol. 22, Issue 3, pp.523-535, 2006

◮ [3] Bo Liu, Junbo Fan Jun Zhou Kui Ki, Yongzhao Xie, "A

Self-Localization Method through Pose Point Matching for Autonomous Soccer Robot Based on Omni-Vision", the 9th International Conference on Electronic Measurement and Instruments, pp.4-246 - 4-249, 2009

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Sources

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ [4] Shu-Yin Chiang, Xingzhi Guo, Hsien-Wen Hu, "Real Time

Self-Localization of Omni-Vision Robot by Pattern Match System", 2014 International Conference on Advanced Robotics and Intelligent Systems, Taipei, Taiwan, 2014

◮ [5] Shu-Yin Chiang, Chi-An Wei, Ching-Yi Chen, "Real-Time

Self-Localization of a Mobile Robot by Vision and Motion System", International Journal of Fuzzy Systems, Vol. 18, No. 6, 2016

◮ [6] https:

//en.wikipedia.org/wiki/Omnidirectional_camera

◮ [7] https://en.wikipedia.org/wiki/Omnidirectional_

camera#/media/File: Omnidirectional_camera_numbered.PNG

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Sources

Motivation Soccerrobot Omnidirectional Camera Possible Preprocessing Monte Carlo Method Field Geometry Usage Conclusion Sources

◮ [8] R. Siegwart, I. R. Nourbakhsh, "Introduction to

Autonomous Mobile Robots", pp.181-188, The MIT Press, Cambridge, Massachusetts, 2004

◮ [9] Dan Xiong, Junhao Xiao, Huimin Lu, Zhiwen Zeng, Quingua

Yu Kaihon Huang, Xiadong Yi, Zhiqiang Zheng, "The Design

  • f an Intelligent Soccer-Playing Robot", Industrial Robot: An

International Journal„Vol. 43, No. 1, pp. 91-102, 2016

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