Relative Bearing Estimation using Commodity Radios

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Relative Bearing Estimation using Commodity Radios. Karthik Dantu 1 Prakhar Goyal 2 Gaurav S. Sukhatme 1. 1 Dept of Computer Science University of Southern California Los Angeles, CA - 90089-2905. 2 Dept of Computer Science and Engg. Indian Institute of Technology-Bombay Mumbai - 400237. - PowerPoint PPT Presentation

Transcript of Relative Bearing Estimation using Commodity Radios

Relative Relative Bearing Bearing

Estimation Estimation using using

Commodity Commodity Radios Radios

Karthik Dantu1

Prakhar Goyal2

Gaurav S.

Sukhatme1

1Dept of Computer Science University of Southern CaliforniaLos Angeles, CA - 90089-2905

2Dept of Computer Science and Engg.Indian Institute of Technology-Bombay

Mumbai - 400237

22/21/21

What is Relative Bearing?

A

B

AB

BA

33/21/21

Uses of Relative Bearing

• Robot Localization (Briechle 04, Chintalapudi 04, Das 02,

Martinelli 05, Niculsecu 03, Spletzer 01, Taylor 07)

• Navigation (Bekris 04, Ducatelle 08, O’Hara 08)

• Topology Control (Eren 03, Li 05, Poduri 08)

• Formation Control (Das 02, Mostagh 08, Spletzer 01)

• Pursuit-Evasion Games (Karnad 08, Maloy 95)

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Measuring Relative Bearing

Directional sensor array

Transmitter array (acoustic, radio)

Vision

Bumper array

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Radio as a Sensor

• Signal strength roughly

correlated with distance

between sender and receiver

• Most modern robots have

off-the-shelf radios

• Radio characteristics are well

studied

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Large Scale Fading

• Radio behavior over

large distances (>> )

• Correlated to distance

• Modeling less reliable

for shorter distances

and very close to

transmitter

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Small Scale Fading

Blue signal travels 1/2 farther than red to reach receiver, who receives purple

Sender Receiver

• Signal variability on the scale of

• Multipath effects dominate (reflection, refraction, diffraction, scattering)

• Mobility introduces Doppler effects

• ~ 12cm for 2.4 GHz

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Large Scale Fading Models

• Free Space Model: Models signal strength on a clear

unobstructed link

LossdB=20log(d) + 20 log(f) + C

• Log Distance Path Loss Model: Logarithmic path loss

model with Path Loss Exponent () for the particular

medium

LossdB= PL(d0)+ 10log(d/d0) + XBg

• ITU Indoor Model: Takes into account the frequency of

transmission and floors between sender and receiver

LossdB= 20log(f) + Nlog(d) + Lf(n) + K

Introduction to RF Propagation, John S. Seybold, Wiley-Interscience.

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Estimating Bearing Using Radio

• Consider only large scale fading effects

• Sample signal strength in the locality of robot

• Perform Principal Component Analysis (PCA)

• Primary component is the direction of maximum

variance of signal strength

• Relative bearing of robot is approximated to this

direction

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Bearing Estimation Algorithm

A

B

S - step sizeS

45° CCW

1111/21/21

Step Distance

• Step distance is a parameter

• Greater step distances improve signal gradient

but odometry error and area of deployment

are constraints

• From our signal strength measurements, for a

signal strength loss of 20dB step size is 6m

outdoors and 2m indoors

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Simulation Setup

• Simulated an area of 100m x 100m

• Two robots are randomly placed in the given

area

• Parameters

• Step distance

• Number of samples collected

• AWGN Noise added to samples collected

• Results are averaged over 100 trials

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Effect of Step Distance Variation

6m

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Effect of Number of Samples

100 samples

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Effect of Noise

1616/21/21

Experimental Setup

iRobot Create

~3 ft

Telos B Mote for ZigBee radio

Wi-Fi Antenna

E-box with Intel 800Mhz PC with 802.11 Wi-Fi card

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Bearing Error Outdoors

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Bearing Error Indoors

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Outdoor Multi-robot Experiments (5 robots)

Edge Actual

Angle

Estimated

Angle

Bearing

Error

1 120° 103.7 ° 12.3 °

2 135° 104.8° 30.2°

3 45° 58.8° 13.8°

4 -30° -11.8° 18.2°

5 -150° -130.7° 19.3°

6 0° 25.8° 25.8°

Average error over two trials was 19.1°

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Indoor Multi-robot Experiments (5 robots)

Edg

e

Actual Angle Estimate

d Angle

Estimatio

nError

1 5° 9.3° 4.3°

2 120° 148.1° 28.1°

3 -160° -147.2° 12.81°

4 170° 202.5° 32.5°

5 -30° -18.3° 11.7°

6 150° 172.1° 22.1°

Average error over 5 trials was 24.3°

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Conclusions

• Relative bearing can be estimated using commodity radios

• Tested algorithm in simulation and experiment

(ZigBee and Wi-Fi)

• Used this estimation as input for connectivity algorithm

• ZigBee radios perform better than Wi-Fi on average

• Average error is approximately 20° indoors and 25°

outdoors using ZigBee radios

• Future work: Exploit small scale effects

2222/21/21

Backup Slides

2323/21/21

Discussion

• Use

2424/21/21

Bearing Estimation Algorithm

A

B

S - step sizeS

2525/21/21

Bearing Estimation Algorithm

A

B

S - step sizeS

45 CCW