Particle Filter Localization for AUVs

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Ed Kelley

Senior thesis presentation

Technologie

ParticleFilterLocalization
forAutonomousAUVs
UsingAugmentedRealityTags
Ed Kelley, 2013
Szymon Rusinkiewicz

This
statue
is
cool
http://www.asergeev.com/pictures/archives/2007/572/jpeg/05.jpg

Iwanta3dmodel
http://www.asergeev.com/pictures/archives/2007/572/jpeg/05.jpg

Video Games
Virtual Reality
Movies
Archeology
Architecture
Maps
Crash Scenes

Manual Modeling?
Laser Scanner?
Multi-View Stereo?
MicrosoftKinect?

AR.Drone2.0
http://ardrone2.parrot.com/photos/photo-album/

Kalman Filter?
Grid Based Markov?
ParticleFilter?

PredictionStepUpdate the position of each particle
using noisy velocity and gyroscope
readings.

CorrectionStep
1. Check for an augmented reality tag.
2. Calculate transformation from
camera to tag.
3. Use known coordinates of the tag to
calculate the position of the quadcopter.

CorrectionStep
4. Weight the particles using their similarity
to this calculated position.
5. Perform weighted resampling of the
particles.
6. With some probability, replace particles
with this calculated position.

Estimate
Use a linear combination of the particle
values to create an estimated pose.

Particlefilterlocalizationusing
augmentedrealitytags
performssubstantiallybetter
thanintegratedvelocityalone.

Next steps...
Fullintegrationwithcontroller.
Modelingobjects.

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Particle Filter Localization for AUVs

1. ParticleFilterLocalization forAutonomousAUVs UsingAugmentedRealityTags Ed Kelley, 2013 Szymon Rusinkiewicz

2. aka

3. Where is the Quadcopter?

4. Motivation

5. This statue is cool http://www.asergeev.com/pictures/archives/2007/572/jpeg/05.jpg

6. Iwanta3dmodel http://www.asergeev.com/pictures/archives/2007/572/jpeg/05.jpg

7. Video Games Virtual Reality Movies Archeology Architecture Maps Crash Scenes

8. Manual Modeling? Laser Scanner? Multi-View Stereo? MicrosoftKinect?

9. Manual Modeling? Laser Scanner? Multi-View Stereo? MicrosoftKinect?

10. Irschara et al. 2010

11. Easy Cheap Complete HighQuality

12. Quadcopters!

13. RelatedWork

14. Irschara et al.

15. Engel et al.

16. Bills et al.

17. SystemDesign

18. AR.Drone2.0 http://ardrone2.parrot.com/photos/photo-album/

19.

20. Localization+Controller=Autonomy

21. Localization

22. Local drift. tend to measurements

23. NoGPS Norangefinders

24.

25. Kalman Filter? Grid Based Markov? ParticleFilter?

26. Kalman Filter? Grid Based Markov? ParticleFilter?

27. . Thisis aparticle

28. . Itrepresents apossible pose

29. . x y z heading weight

30. PredictionStepUpdate the position of each particle using noisy velocity and gyroscope readings.

31. CorrectionStep 1. Check for an augmented reality tag. 2. Calculate transformation from camera to tag. 3. Use known coordinates of the tag to calculate the position of the quadcopter.

32. CorrectionStep 4. Weight the particles using their similarity to this calculated position. 5. Perform weighted resampling of the particles. 6. With some probability, replace particles with this calculated position.

33. Estimate Use a linear combination of the particle values to create an estimated pose.

34. Testing

35. Gyroscope

36. Ultrasound

37. AR Tag

38. AR Tag

39. AR Tag

40. AR Tag

41. ManualFlightTest

42.

43.

44.