SLAM PSanthanam

7/21/2019 SLAM PSanthanam

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Simultaneous Localization &Mapping - SLAM

Praveen K Santhanam – pks6



NUT SHELL

SLAM is a technique used to buildup a map within an unknownenvironment or a knownenvironment while at the same timekeeping track of the currentlocation



To a human

Assume !ou are blindfolded in aroom



What is SLAM?

o "he problem has # stages$ Mapping

$ Locali%ation

o "he parado&'$ (n order to build a map) we must know our

position

$ "o determine our position) we need a map*

o SLAM is like the chicken+egg problemo Solution is to alternate between the two

steps



SLAM – Multiple parts

Landmark e&traction data association

State estimation state update landmark update

"here are man! wa!s to solve each of

the smaller parts



Har!are

Mobile ,obot

,ange Measurement -evice

$ Laser scanner – .A//0" be usedunderwater

$ Sonar – /0" accurate

$ 1ision – .annot be used in a room with

/0 light



The goal o" the process

"he SLAM process consists of number of steps

o 2se environment to update the position of the robotSince the odometr! of the robot is often erroneous wecannot rel! directl! on the odometr!

o 3e can use laser scans of the environment to correct theposition of the robot

o "his is accomplished b! e&tracting features from theenvironment and re observing when the robot movesaround



E#tene $alman %ilter

An 4K5 4&tended Kalman 5ilter7 is the heart of the

SLAM process o (t is responsible for updating where the robot thinks

it is based on the Landmarks features7

o "he 4K5 keeps track of an estimate of theuncertaint! in the robots position and also theuncertaint! in these landmarks it has seen in the

environment



'er'ie!

Laser Scans

0dometr! .hange

4K5 /ew0bservations

4K5 ,e+observation

4K5 0dometr! update

-ata Association

Landmark 4&traction



Laser & ometr( ata

Laser data is the reading obtainedfrom the scan

"he goal of the odometr! data is toprovide an appro&imate position ofthe robot

"he difficult part about the

odometr! data and the laser data isto get the timing right



Lanmar)s

Landmarks are features which caneasil! be re+observed anddistinguished from the environment

"hese are used b! the robot to findout where it is to locali%e itself7



The )e( points a*out suita*le Lanmar)s

o Landmarks should be easil! re+observable

o

(ndividual landmarks should bedistinguishable from each other

o Landmarks should be plentiful in theenvironment

o Landmarks should be stationar!



(n an indoor environment such as that used b! our robot there areman! straight lines and well defined corners "hese could all be used

as landmarks



Lanmar) E#traction

0nce we have decided on whatlandmarks a robot should utili%e weneed to be able to somehow reliabl!e&tract them from the robotssensor! inputs

"he # basic Landmark 4&traction

Algorithms used are Spikes and,A/SA.



Spi)e

o "he spike landmark e&traction uses e&trema to find landmarks

o when some of the laser scanner beams reflect from a wall andsome of the laser scanner beams do not hit this wall) but arereflected from some things further behind the wall

Spike landmarks "he red dots are table legs e&tracted as landmarks

Spike landmarks rely on the landscape changing a lot between two laserbeams. This means that the algorithm will fail in smooth environments.



+ANSA, +anom Sampling ,onsensus.

"his method can be used to e&tract lines from alaser scan that can in turn be used as landmarks

,A/SA. finds these line landmarks b! randoml!

taking a sample of the laser readings and then usinga least squares appro&imation to find the best fitline that runs through these readings

.onsensus



/ata Association

"he problem of data association is that ofmatching observed landmarks fromdifferent laser7 scans with each other

Problems in -ata Association 8ou might not re+observe landmarks ever! time

8ou might observe something as being a landmark butfail to ever see it again

8ou might wrongl! associate a landmark to apreviousl! seen landmark



Algorithm – Nearest Neigh*our Approach

3hen !ou get a new laser scan use landmarke&traction to e&tract all visible landmarks

Associate each e&tracted landmark to the closestlandmark we have seen more than / times in the

database Pass each of these pairs of associations e&tracted

landmark) landmark in database7 through avalidation gate (f the pair passes the validation gate it must be the same

landmark we have re+observed so increment the number oftimes we have seen it in the database

(f the pair fails the validation gate add this landmark as a newlandmark in the database and set the number of times wehave seen it to 9



'er'ie! o" the process

2pdate the current state estimateusing the odometr! data

2pdate the estimated state from re+observing landmarks

Add new landmarks to the currentstate



%inal +e'ie! – pen Areas

"here is the problem of closing the loop"his problem is concerned with the robotreturning to a place it has seen before

"he robot should recogni%e this and usethe new found information to update theposition

5urthermore the robot should update the

landmarks found before the robotreturned to a known place) propagatingthe correction back along the path



+e"erences

Slam for dummies) b! Soren,iisgaard : Morten ,ufus ;las

3ikipedia + Slam Minimal Slam for 4fficient 5loor+

Planning) b! Stephen Pfetsch

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SLAM PSanthanam

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