An MPEG-Processor-based Robot Vision System for Real-Time De(3)

This paper describes a PC-based vision system that can be used to detect moving objects from a mobile robot. An image processing board equipped with an MPEG motion estimation processor calculates a sparse but robust optic flow in real-time. An algorithm to

pleobjectsorbigdisplacements(astypicallyinducedbycamerarotation)a xedblock-rasterisnotadequate.Toachievethehighestpossible exibility,thecoordinatesofRBsandSWscanberandomlysetbythesoftwarerunningonthePCforeachsinglematchingoperation.Alistof

positions

isreadviaDMA,thelistofresultsiswrittenbackbyDMAagain.ThissavesmostoftheCPU’sprocessingpowerfortheapplicationsoftwarethatevaluatesthegenerated ow eldsasdescribedinthenextsection.Foramoredetaileddescriptionofthehardwaresee[7].

3Detectionofmovingobjectsbyoptic owsegmentation

Manypapersintheliteratureofoptic owaddresstheproblemofobjectsegmentationandmotionparameterre-construction.Algorithmstocalculateall veparameters(theabsolutevalueofthetranslationvectorgetslostdur-ingthe3Dto2Dprojection)wereproposedforexamplebyPrazdny[6]orWengetal.[8].Adivpresentsanelegantap-proachtosolvethesegmentationproblemforall veparam-eters:Objectsareconsideredtoconsistofplanarsurfaces,sovectorscanbeclusteredinan8D(5Dforthemotionand3Dforthesurfaceparameters)Houghspace[1].

Applyingthesetechniquestooptic owscalculatedbyoursensorsystemproducesnosatisfyingresults,though.ResponsibleforthefailureoftheseverygeneralapproachesisthenumericalinstabilityoftheclosedformsolutiontoEqn.1alongwiththestrongquantizationerrorsofthecal-culatedvectors.

Thereasonforthisfailurecanalsobegraphicallyde-ducedbythesimilarityof eldsgeneratedbymerelateralandmererotationalmotion.Thoughallvectorsarepar-allelinthetranslationalcase,andalignedwithhyperbolas(accordingtoEqn.1)intherotationalcase,thedifferencehasthesameorderofmagnitudeasthequantizationeffects.Fig.4demonstratestheproblemforrealisticcameraparam-etersandconstant

depth.

Figure4.Optic ow:a)horizontaltranslation

b)verticalrotation.

Therefore,ageneralsolutiontothecompletemotionre-covery(i.e.segmentationofmovingobjectsanddetermina-tionofall5parametersforeachobject)seemsimpossible

inourcontext.

Morepragmaticapproachesthatcluster owvectorsalongtheir2DpropertiesasforexampleproposedbyYa-mamotoetal.[9],producedbetterresults,butaredif culttoadaptforamovingobserverandcannotbeusedforob-jectsmovingalongtheopticalaxis.

3.1Determinationofego-motion

Becauseoftheaboveproblems,weintroducesomesim-pli cationstothegeneralapproachesthatareinspiredbytherequirementsofourapplication.Becausethecameraismountedonamobilerobotwithnon-holonomickinemat-ics,onlyonetranslationalandonerotationalparameterre-main.Withoutfurtherrestrictinggenerality,buttosimplifytheequations,itisassumedthatthecameraismountedhori-zontally.Incameracoordinates,thereis

andthegeneralequationoftheoptic ow(Eqn.1)canbereducedtothefollowing:

and)remain,

Eqn.4canbesolvedforeachvectorasfollows:

(5)

isameasurementofthedistanceof

thecorresponding3Dpointandthushasanindividualvalueforeachvector(itisthereciprocalvalueoftheTimeToCollision,TTC).

Thesecondresult

shouldcorrespondtotherotationalvelocityofthecameraandthereforebeidenticalforeachvector.Thus,therotationofthecameracanbeestimatedbyasimplemeanvaluecalculation:

(7)

ExperimentsonMARVINinarealof ce-typeenviron-menthavedemonstratedthefeasibilityoftheproposedes-timationapproachfor.Whenemployingthemedianin-steadofthesimplemeanvalue,therobustnessofthecal-culatedvalueagainstremainingfaultyvectorscanbein-creasedfurther.Fig.5showsacomparisonoftheestimatedandtheonecalculatedbytheodometryoftherobot.Sincetheresultingvectorlengthsigni cantlyexceedsthemaximalvectorlengthoftheMEP,evenformoderateturningratesoftherobot(