Institute of Systems Optimization · Institute of Systems Optimization Combining Laser Range...

Institute of Systems OptimizationInstitute of Systems Optimization

Combining Laser Range Measurements and a Dual-IMU IPNS

Dipl.-Ing. Christian Ascher

g gfor Precise Indoor SLAM

p gDipl.-Ing. Christoph KeßlerProf. Gert Trommer

www.ite.uni-karlsruhe.deInstitute of Systems Optimization

Motivation

Dual-IMU Integrated Pedestrian Navigation System (IPNS)

DRDR

High accuracy with Zero Velocity Updates on the foot

Dynamics of torso mounted VISION sensor DRDR

ZVU

Tight integration with VISION

Example: ZVUZVUExample:

Combining with LASER measurements

ZVU

IMULaser

Christian Ascher 03.08.2009Institute of Systems Optimization1

Agenda

Integrated Pedestrian Navigation System (IPNS)

Dead Reckoning(DR) & Zero Velo Updates(ZVU)

Dual-IMU approach

OrthoSLAM

OrthoSLAM Algorithm from V.Nguyen, ETH Zurichg g y ,


ConclusionConclusion

Christian Ascher 03.08.20092 Institute of Systems Optimization

Dead Reckoning and Zero Velocity Update

StrapdownAlgorithmusAlgorithmus

IMU Corrections Nav-Sol

Up

NorthCovariance approx.

Kalman FilterPDRtorso:

PDRPDR

mk−ΨkΨ

2D-Pos,kKalman Filter16 stateZVUfoot:

2D-Pos,k-m

ZVU

indoor

MAGGPS BAROEast


Foot vs. Torso

ADIS16355

Time = 10 minDi t 850

Torso

thth

Distance = 850m

Nor

tN

ort

Foot

East

East Reference


Quelle: Google Inc., Google Maps

Foot vs. Torso

ADIS16355Torso DR:stairst l thstep length wrong

rth

Torso

Nor

Foot

East

Mean relative length error

Torso: 3.41%


Quelle: Google Inc., Google Maps Foot: 1.58%

Zero Velocity Update

ADIS16355

Indoor (reinforced concrete)Indoor (reinforced concrete)

Torso

h (1

4m)

Nor

t

FootEast (30m)

Mean relative length error:

Torso: 5.20%


Fuß: 2.34%

Dual-IMU IPNS: Combining individual advantages

BarometerMagnetic field0

5

0

5

0

5

0

5 Height information curve dynamics

1

1.5

2Baro

met

ers

1

1.5

2Baro

met

ers

1

1.5

2Baro

met

ers

1

1.5

2Baro

met

ers

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Magfield in a building

TorsoFootN

10

-5

ter

-5

0

ter

10

-5

ter

-5

0

ter

FootTorso Combination

of individual

0 5

0

0.5

1

Dow

n/in

vers

e in

0 5

0

0.5

1

Dow

n/in

vers

e in

0 5

0

0.5

1

Dow

n/in

vers

e in

0 5

0

0.5

1

Dow

n/in

vers

e in

Referenz-15

-10

Dow

n in

me

-15

-10

Dow

n in

me

-15

-10

Dow

n in

me

-15

-10

Dow

n in

me

ZVUV=0N

orth

Nor

th

of individual advantages

DUAL-IMU IPNS

23.4 25.35 27.3 29.25 31.2 33.15-1

-0.5

time in s

D

23.4 25.35 27.3 29.25 31.2 33.15-1

-0.5

time in s

D

23.4 25.35 27.3 29.25 31.2 33.15-1

-0.5

time in s

D

23.4 25.35 27.3 29.25 31.2 33.15-1

-0.5

time in s

D

S-25

-20

-20

15

-25

-20

-20

15

Foot TorsoFoot Torso

-5 0 5 10 15-30

-5 0 5 10-25

-5 0 5 10 15-30

-5 0 5 10-25 East

East


Dual-IMU IPNS - conceptOnboard

IMU

ω

aω

VISION

Kalman Filter + Strapdown

SLUSLUSLUΨ update

KF+

mon

,aωVision update

TorsoSLUSLUSLU

tktk+1tk+2

update

Step length update(left foot)update

ZVUZVUZVUKalman Filter + Strapdown

HeightΔ

( )p(right foot)

V=0V=0V=0+ Strapdown

Foot Zero velo update

ADIS16355 (right foot)


Dual-IMU IPNS – system setup Mag

Gyro

Baro

Acc

NavBoard

Laser

Hokuyo URG-04LX Laser- range: 4.5m- opening angle: 240°

Acc

Torso: NavBoard- self-developed sensorboard- 2 Kalmanfilters running opening angle: 240- Navsolution output

ADIS16355

Foot: ADIS16355- self-developed

Handheld: Openmoko- display and operation


p- Bluetooth connection

p y p- map matching (particle filter)

Dual-IMU IPNS – results II

800

900TorsoDual-IMU IPNS

600

700

800 Dual IMU IPNSReferenceDual-IPNS Solution

- !!Torso Solution!!- accuracy of foot (ZVU)- dynamics of torso/VISION

Onboard IMU

400

500

Nor

th

- dynamics of torso/VISION- can directly be combinedwith VISION sensors

Onboard IMU

dual updates

100

200

300

20m

2rs)

Höhe DualHöhe

ADIS16355

200 400 600 800 1000

100

East

20m

0 20 40 60 80 100 120 140 160-2

0

time in sec

Up

(met

e


Dual-IMU IPNS – results III

Dual-IMU IPNSReferenceDual-IPNS Solution

!!T S l ti !!- !!Torso Solution!!- Results are reproductive

NavBoard 4mNavBoard

dual updates

14

ADIS16355

30m


Dual-IMU IPNS - conceptOnboard

IMU

ω

aω

VISIONVISION

Kalman Filter + Strapdown

SLUSLUSLUΨ

KF+

mon

,aωVision update

TorsoSLUSLUSLU

Step length update

update

ZVUZVUZVUKalman Filter + Strapdown

HeightΔ

update

V=0V=0V=0+ Strapdown

Foot Zero velo update

ADIS16355


Agenda

Integrated Pedestrian Navigation System (IPNS)

Dead Reckoning(DR) & Zero Velo Updates(ZVU)

Dual-IMU approach

OrthoSLAM

OrthoSLAM Algorithm from V.Nguyen, ETH Zurichg g y ,


ConclusionConclusion


Ortho SLAM

Basis of OrthoSLAMBasis of OrthoSLAM

„Orthogonal SLAM: a Step toward Lightweight Indoor Autonomous

Navigation” 2006 Viet Nguyen et al ETH ZürichNavigation 2006, Viet Nguyen et al., ETH Zürich

Realization

R d ti f l it b li iti b ildi t th l liReduction of complexity by limiting building to orthogonal lines

State vector only with line distances

Using a local mapto reduce search area


OrthoSLAM Algorithm

Schematic of OrthoSLAM algorithmSchematic of OrthoSLAM algorithm

NewNew sensordata

Preprocessing Line extraction Data assoziation Orthogonalization

Pos updateLine-Merger

B

d1

Line 1

Mapping DistanceEstimation (KF)

Baseline

Line 2

Line 3

d2

d3

„Orthogonal SLAM: a Step toward Lightweight Indoor Autonomous Navigation” 2006, Viet Nguyen et al., ETH Zürich


OrthoSLAM – results


OrthoSLAM – results with long corridor

Problem: - long corridor

t l li- no transversal lines

Navsol

Map


OrthoSLAM –using Dual-IMU IPNS

Solution: - Dual-IMU IPNS support

d t IPNS idi

Problem: - long corridor

t l li

y [mm] [ ]

- green dots = IPNS aiding- no transversal lines

y [mm] y [mm]

IPNS-aidingaiding

mit IPNSohne IPNS

x [mm] x [mm]

Christian Ascher 03.08.200918 Institute of Systems Optimization18


Combining LASER and IPNS is necessary in long corridors

Yields to good accuracy (example 2% mapping error)

Combined system is much more robust

Loop closure

Map NavSol[mm][mm]

real17 30 ti t d17.30 m estimated

17.00 m

[mm][mm]


Conclusion

Dual-IMU Integrated Pedestrian Navigation System (IPNS )

f f t (ZVU)accuracy of foot (ZVU)

dynamics of torso/VISION

can directly be combined with VISION sensors

Combining Laser measurements and a Dual-IMU IPNS

OutlookOrthoSLAM online processing on a portable Intel Atom

Combining Camera with Dual-IMU approachg pp

Portable System for operators


The end

Thank you.

Feel free to ask questions!

Institute of Systems OptimizationUniversity of Karlsruhe , Germany

Dipl.-Ing. Christian AscherDipl. Ing. Christian AscherDipl.-Ing. Christoph KeßlerProf. Gert Trommer


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