(ii)if i∈{1,...,n}, p[i] MBC(p[1]···p[n]) 2≤
rctr,thenthesolutionofMTR(Ecmpl,B(0,rctr))isgivenbyp(T)=prndzvs,disk,prndzvs,disk∈∩i∈{1,...,n}B(p[i],rctr),andu[i](t)=prndzvs,disk p[i](t).
Alternatively,ifu[i]∈C(0,rctr),i∈{1,...,n},then
(iii)p(T)=prndzvs,cube,prndzvs,cube∈RMT,ua[i](t)=
min{rctr,|prndzvs,a pa[i](t)|}sign(prndzvs,a pa[i](t)),i∈{1,...,n},a∈{1,...,d}isasolutionofMTR(Ecmpl,C(0,rctr)),where
RMT= MOC(p[1](0),...,p[n](0))
1
a
2
(lmax la)
,
lmaxisthelargestsideofMEO(p[1](0),...,p[n](0))andlaisthesideindirectiona;
(iv)if i∈{1,...,n} p[i] MOC(p[1]···p[n]) ∞≤rctr
thesolutionofMTR(Ecmpl,C(0,rctr))isgivenbyp(T)=prndzvs,prndzvs∈∩i∈{1,...,n}C(p[i],r]ctr),andu[i(t)=prndzvs p[i](t). IV.DISTRIBUTED
CONSENSUSONMINIMALENCLOSING
BALLANDORTHOTOPE
Intheprevioussectionwehaveshownthatminimalenclosingshapesplayakeyroleinthesolutionofminimumtimerendezvous.Infactiftheagentscouldknowthecenterofsuchshapes(ballororthotope)thesolutionofminimumtimerendezvouswouldbejustacontrollawthatdriveseachagenttothispoint.Therefore,inthissection,wewanttoexploretwoconsensusalgorithmstocomputetheminimalenclosingballandtheminimalenclosingorthotopeofasetofgivenpointsinRdinadistributedway.
HereisaninformaldescriptionofwhatweshallrefertoastheFloodMEBalgorithm:
[Informaldescription]Eachagentinitializestheminimalenclosingballtoitsinitialposition,then,ateachcommunicationround,performsthefol-lowingtasks:(i)itacquiresfromitsneighbors(amessagerepresentedby)thecoordinatesoftheminimumsetofpointsdescribingtheboundaryoftheirminimalenclosingballandthecoordinatesoftheirinitialposition;(ii)itcomputestheminimalenclosingballofthepointsetcomprisedofitsanditsneighbors’setofpointsanditsinitialposition(thatitmaintainsinmemory);(iii)itupdatesitslogicvariablesandmessageasin(i).
Beforedescribingthealgorithmmoreformally,weneedtointroducesomenotationandstatesomepropertiesoftheminimalenclosingball.Givenasetofmpoints{q1,...,qm} Rdingenericpositions,wedenotewithMEBbndry({q1,...,qm})theminimumsetofpointsontheboundaryofMEB({q1,...,qm})thatuniquelyidentifysuchboundary.Whenthepointsareingenericposition,weletMEBbndry({q1,...,qm})denoteaminimumsetofpointsontheboundaryofMEB({q1,...,qm})thatidentifysuchboundary.Moreover,letMBR:F(Rd)→Rthefunction
thatassociatestoasetofpointstheradiusoftheminimalenclosingballofsuchpoints.
Lemma4.1(MEBproperties):LetQnasetofnpoints.Thefollowingstatementshold.
(i)thereexistsasubsetQd Qnofd+1elementssuch
thatMEB(Qd)=MEB(Qn);
(ii)forallQn1,Qn2 QnwithQnQ;
1 Qn2,then
MBR(n(iii)ifMBR(Q1)≤MBR(Qn2)nQ1)=MBR(Qn2),thenMBC(Qn1)=
MBC(n(iv)thenumber2);
ofpossiblevaluesofMBR(Qn Q1),forall
Qn1n,is nite.
Remark4.2:AnimportantimplicationofLemma4.1(i)isthatMEBbndry({q1,...,qn})hasatmostd+1points,thenthenumberofpacketsinthemessagesentandstoredbyeachagentisatmostd+1anddoesnotdependonn. :FloodMEBalgorithm.
Goal:Solvetheproblemofcomputingmin-imalenclosingballofasetofLogicstate:w[i]=(P[i]bndry,p[i]
points.
0);Msgfunction:msg(x[i],w[i],i)=w[i];Initialization:
P[i]bndry(0)={p[i](0)},p[i]
0(0)=p[i](0).
In this paper we introduce the notion of optimization under control and communication constraint in a robotic network. Starting from a general setup, we focus our attention on the problem of achieving rendezvous in minimum time for a network of first order
sequencecorrespondstoaballwhoseradiusismonotonenondecreasing,upperboundedandcanassumea nitenum-berofvalues.Thenweproceedbycontradictiontoprovethatallthelawsconvergetothesameball(sameradiusandcenter)andthatitisexactlytheminimalenclosingballofthenpoints.Supposethatthealgorithmconvergesondifferentballs(differentradiusordifferentcenter)fordifferentagents.Thentheremustexisttwoagentsthatareneighborsandhavedifferentlogicvariables(correspondingtodifferentballs).Butthismeansthat,atthefollowingtimeinstant,theyhavetocomputetheminimalenclosingballofalargersetofpoints,theneitheroneofthemwilltakethevalueoftheotherorbothofthemwillchangetheirvalueandtakeacommonone.Iteratingthisargumentweobtainthatalltheagentsmustconvergetoacommonvalue.Now,theballateachnodecontains,byconstruction,theinitialpositionofthatnode.Sincetheballisthesameforeachnode,itcontainsalltheinitialpositions,thenitistheminimalenclosingballoftheinitialpositions.
Fori∈{1,...,n},agentiexecutesateachtimet∈N:
1:acquirew[j],j∈N(i)2:
compute a∈{1,...,d}
p[i]
=minj∈N(i)∪{i}{p[j]min,a(t+1)p[max,ai]min,a(t)}(t+1)=maxj∈N(i)∪{i}{p[max,aj]
(t)}3:
update a∈{w[ai](t+1)= 1,...,d}p[i]
p[max,ai]min,a(t+1),(t+1)
whereimin,aandimax,aaretheagentsthatcharacterizetheboundaryoftheorthotopeindirectionaandminimizethetopologicaldistancefromi.
ThetimecomplexityofthealgorithmisoforderΘ(n). Proof:InordertoprovethecorrectnessandthetimecomplexityofthealgorithmdescribedinTable??,weneedtoprovethatitisequivalentto2dFloodMaxalgorithmsforleaderelection(twoforeachdirection)runningsimultane-ously.Oncewehaveproventhat,theresultsoncorrectnessandtimecomplexityfollowfromChapter4in[1].
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