RESOURCE SCHEDULING STRATEGIES FOR A NETWORK-BASED AUTONOMOUS MOBILE ROBOT. Hongryeol Kim, Joomin Kim, and Daewon Kim

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1 RESOURCE SCHEDULING SRAEGIES FOR A NEWORK-BASED AUONOMOUS MOBILE ROBO Hongyeol K, Joon K, and Daewon K Depatent of Infoaton Contol Engneeng, Myong Unvesty Abstact: In ths pape, effcent esouce schedulng stateges fo a netwok-based autonoous oble obot wth hybd obot contol achtectue ae poposed. he bass of the esouce schedulng stateges s the DMS(Deadlne Monotonc Schedulng), and soft deadlne and had deadlne ae newly defned wt the DMS. A coodnated schedulng stategy confgues the soft deadlnes consdeng poceedng constants fo the nzaton of behavo-to-behavo delays. A odulaton stategy of the had deadlnes-ates s also poposed n ths pape fo the optal usage of coputatonal esouce. he odulaton s pefoed based on the dynacal values of the behavos unnng on an opeatng syste n each node. o copensate the uncetanty of the dynacal values nfeed by senso nfoaton, the fuzzy contols ae used fo the odulaton, and the genetc algoth s also used to efne the ate odulaton esult consdeng optal eal-te feasblty. hough sulaton tests, schedulng esults wth the poposed stateges ae copaed wth esults wthout the poposed stateges to vefy the pefoance enhanceent by the poposed stateges. Copyght 2005 IFAC Keywods: behavo, schedulng, netwok, obot, deadlne, odulaton, fuzzy contol, genetc algoth. INRODUCION Vaous studes have been pefoed on netwokbased systes, snce they enable conuncton of vaous heteogeneous systes and also nze the cost fo the conuncton. Recently, these studes ae extendng to such coplcated systes as autonoous oble obots fo seveal puposes. Snce ost oden autonoous obots have hybd obot contol achtectues(r.ala, et al, 998) (R.C.Akn, and. Balch, 997)(Hongyeol K, et al., 2004) fo both of plannng capablty and behavoal actvty, a study fo the hybd obot contol achtectue on netwok-based syste s also beng pefoed(kiech, 2004). Snce the hybd contol achtectues ae based on paallel coputng envonent, coputatonal esouce schedulng s vey potant fo the contol achtectue. But unfotunately, coputatonal esouce schedulng on each ndependent node ntegated wth councaton schedulng has possblty to bng unacceptable delay fo the obot contols wth the netwok-based obots. Addtonally fo the coecalzaton of the obots, the capacty of the coputatonal esouces wll be constaned fo copettve cost. Consequently, the nzaton of the delay on the netwok-based syste and optal allocaton of the coputatonal esouce ae equed fo the netwok-based autonoous oble obot. In ths pape, effcent esouce schedulng stateges fo a netwok-based autonoous oble obot wth hybd obot contol achtectue ae poposed. he bass of the esouce schedulng stateges s the DMS(Deadlne Monotonc Schedulng), and soft deadlne and had deadlne ae newly defned wt the DMS. A coodnated schedulng stategy confgues the soft deadlnes consdeng poceedng constants fo the nzaton of behavo-to-behavo delays. A odulaton stategy of the had deadlnes-ates s also poposed n ths pape fo the optal usage of coputatonal esouce. he odulaton s pefoed based on the dynacal values of the behavos unnng on an opeatng syste n each node. o copensate the uncetanty of the dynacal values nfeed by senso nfoaton, the fuzzy contols ae used fo the odulaton, and the genetc algoth s also used to efne the ate odulaton esult consdeng optal eal-te feasblty. hough sulaton tests, schedulng esults wth the poposed stateges ae copaed wth esults wthout the poposed stateges to vefy the pefoance enhanceent by the poposed stateges. 2. HYBRID ROBO CONROL ARCHIECURE FOR A NEWORK-BASED ROBO A pctue of a netwok-based autonoous oble obot s shown n Fg.. he obot s an assebly

2 coposed of ban odule, senso odule, anpulato odule, and oble odule. he functonal odules ae nteconnected though the CAN(Contolle Aea Netwok) (Robet Bosch GbH, 99). Senso Module studes devoted to the schedulng stategy wth the abtaton echans of the CAN(K. M. Zube, K. G. Shn, 997)( Mavo D and Natale M., 2000) (Dukn Pae, et al., 2002). In ths study, the DMS s also adopted fo the schedulng stategy of the CAN essage abtaton. Manpulato Module Moble Module Ban Module Fg. Netwok-based Autonoous Moble Robot A thee-teed hybd obot contol achtectue fo the above netwok-based obot, whch s the bass of ths study, s shown n Fg. 2(Hongyeol K, et al., 2004). As shown n the Fg. 2, the contol achtectue s coposed of the plannng laye, the executve laye and the behavo laye. he establshent of esouce schedulng stateges s pefoed by the executve laye. On the behavo laye, the behavos ae pocesses unnng on the ult-taskng opeatng systes. Snce the behavos ae dstbuted ove the netwok syste, ntefaces aong soe behavos ae pefoed though the netwok councaton. Fg. 2. Netwok-based Autonoous Moble Robot 3. IME PROPERIES OF BEHAVIORS AND HEIR INERFACES Snce functon copleton n te s equed fo the obot contols, eal-te schedule should be ounted wth the ult-taskng opeatng systes n the Fg. 2. In ths pape, the DMS s adopted fo the schedulng stategy of the eal-te schedule. Snce schedulng only wth peodc tasks can guaantee the eal-te featue of the DMS, all the behavos ae nvoked peodcally. Real-te schedulng stategy should be also used fo the abtaton of the CAN essage. hee ae any Fg. 3. Behavo-to-behavo Delay Synthess of the delay nvoked whle a essage s geneated fo a behavo, tanstted to anothe behavo, and pocessed by the ecevng behavo s shown n Fg. 3. As shown n the Fg. 3, behavo-tobehavo delay s coposed of fve eleents. he fst two eleents ae delays caused by the opeatng syste schedulng at the tansttng node and the ecevng node( and 5 n the Fg. 3). he delays ae coposed of watng te fo behavos wth hghe potes, blockng te by behavos wth lowe potes, and coputaton te of tself. he wost case of the total delay( ) s epesented by equaton () and (2)( N.C Audesly,, et al., 990). Whee, C and C ae coputaton tes of behavo and ndvdually, B s blockng te of task, s the elease ate of the behavo, hp ( ) s the set of behavos wth hghe potes than behavo, and lp ( ) s the set of behavos wth lowe potes than behavo. C B C hp = + + () ( ) B = MAX (2) K lp( ) k Snce the behavos on a node nvoke peodcally, the bandwdth utlzaton of each behavo s epesented by equaton (3). And fo the eet of suffcent condton of eal-te feasblty, the total bandwdth utlzaton of the peodc behavos s constaned wth equaton (4)(.W.Kuo and A.K.Mok, 997). Whee, B Bs the nube of haonc bases. Snce only deadlne s ctea fo esouce allocaton wth the DMS, the QoS(Qualty of Sevce) of soe behavos, whch ae not ctcal but need hgh utlzaton of coputatonal esouce, cannot be guaanteed. o solve the QoS poble, ate odulaton stategy wll be poposed fo the functon of local esouce anage n the Fg. 2. C U = (3) n = C 2 (4)

3 he second eleent s delay caused by the CAN schedulng stategy wth ts abtaton echans(3 n the Fg. 3). Sla to the delay n opeatng systes as shown n the equaton () and (2), the wost case of the total delay s coposed of watng te n essage queue and tanssson te. he watng te n essage queue ncludes watng te by essages wth hghe poty, and blockng te by essages wth lowe potes. he wost case of the total delay( ) s epesented by equaton (5) and (6) (Dukn Pae, et al., 2002). Whee, C s physcal tanssson te of essage, B s blockng te of essage, s the elease peod of essage, hp ( ) s the set of essages wth hghe potes than essage, and lp ( ) s the set of essages wth lowe potes than essage. + J B C hp( ) = + (5) B = MAX c (6) K lp( ) k he thd eleent s delays caused by asynchonous tng between opeatng syste schedulng and the CAN essage schedulng(2 and 4 n the Fg. 3). In the Fg. 3, n case of essage tanssson fo a behavo n tansttng node to netwok, eal-te opeatng syste n tansttng node s foe step, and the netwok s latte step. Slaly, n case of essage tanssson fo the netwok to a behavo n ecevng node, the netwok s foe step, and eal-te opeatng syste n ecevng node s latte step. Wth the sequental phase stated above, the asynchonous watng delay s nvoked two tes, when a essage fo the opeatng syste n the tansttng node s watng fo tanssson on the netwok, and also when the netwok essage s watng fo handlng by the opeatng syste n the ecevng node. o nze the asynchonous watng poble, a coodnated schedulng stategy wll be poposed fo the functon of global esouce anage n the Fg RESOURCE SCHEDULING SRAEGIES FOR A NEWORK-BASED AUONOMOUS MOBILE ROBO 4. Coodnated schedulng stategy In ths pape, a coodnated schedulng stategy s poposed to educe the asynchonous watng delay, consequently to educe whole behavo-to-behavo delay. Fo the schedulng stategy, new defntons of te popetes of behavos and essages ae shown n the below: Rate( ) Rate s defned as constant condton of ealte of a behavo o a essage. he ate has sae eanng wth the deadlne of the DMS. 2 Release e( R ( k ) ) Release te s defned as the nstant when a behavo o a essage s eady to stat to be pefoed o be tanstted fo dle status. he elease te s defned wth equaton (7). Hee, R 0 eans ntal elease te, and k eans elease tes of the behavo o essage. R ( k ) = ( R0 + k ) (7) 3 Coputaton e( C ) o anssson e( C ) C s coputaton te of behavo. Slaly, C s tanssson te of essage. 4 Deadlne( D ( k )) D ( k ) s not such had deadlne as defned n the DMS, but soft deadlne. he odulaton ange of the soft deadlne s defned as equaton (8). 0 < D ( k) (8) 5 Value( V ( k )) V ( k ) s elatve un-te value of a behavo o a essage at the nstance k. Fg. 4. Onlne Deadlne Assgnent he coodnated schedulng stategy poposed n ths pape s pleented wth onlne assgnent of the soft deadlnes, and the deadlne assgnent( D ( k ) ) n the foe step s detened as R () R(k ) satsfyng R ( ) < R(k ) < R( ) n the latte step as shown n Fg. 4. he poty wth the deadlne assgnent s detened accodng to the value of the foe behavo o essage. Wth the deadlne assgnent pocedue, the adsson contol of the deadlne assgnent s pefoed fo the bahavos fo =, to =n wth the equaton (). Slaly, the adsson contol of essages s pefoed fo the essages fo =, to =n wth the equaton (3). he detals of the pocedue ae descbed n the below: UStepU: Algn behavos o essages n descendng ode of values fo = to =n. UStep2U: Pefo step 2 fo n tes fo = to =n wth followng odes. Step 2-: At nstance k of foe step, fnd of latte step satsfyng R ( ) < R ( k ) < R ( ). Step 2-2: Pefo adsson contol wth new deadlne canddate at nstance k, D ( k ) = R ( ) R ( k ). Step 2-2: Assgn the new deadlne canddate to D ( k ), and pefo Step2 wth +, f the adsson contol s successful. Othewse, pefo Step3.

4 Step3: Pefo step 3 fo n-(-) tes fo =n to =- wth followng odes. When etuned to Step3 agan afte =-, pefo Step2 fo + wth D ( k ) = D ( k ). Step 3-: Pefo adsson contol wth new deadlne canddate at nstance k, D ( k ) =. Step 3-2: Assgn the new deadlne canddate to D ( k ), and pefo Step2 wth +, f the adsson contol s successful. Othewse, pefo Step3 wth Rate odulaton stategy In ths pape, a ate odulaton stategy s poposed fo the optal QoS. he ate odulaton s pefoed on the un-te values of behavos and the essages. he values of the behavos and the essages ae decded by eactve planne on the plannng laye n the Fg. 2. Snce the eactve plane akes decsons wth uncetan peceptons, the values ae also uncetan. o copensate these uncetantes, the local esouce anage has ts own fuzzy contolles to fuzzfy the values decded by the planne. he outputs of the fuzzy contolles ae defuzzfed nto ate odulaton esults. he ate odulaton esults ae efned wthn the allowable DMS constants to get optal esults consdeng haony of the ates. he constucton of coputatonal esouce anage wth abstact eactve plannng closed loop s shown n Fg. 5. d e (,t + dt ) = ( k + ) s(,t )w(, ) (9) dt In the vew of contol theoy, ates of the behavos can affect the stabltes of the behavo contols. Snce ost of cuent behavos ae pleented nto dscete systes, the saplng ate constant fo contol stablty of dscete syste(k.j.asto and B.Wttenak, 997) s adopted n ths pape. hs constant defned wth equaton (0) s used fo the decson of allowable axu and nu ate. Whee, s syste sng te of BthB task. 4 0 (0) he ate odulaton esults fo the fuzzy contols should be efned to eet to antan ts contol stablty and to keep eal-te constants defned wth the equaton () and (4). In ths pape, the genetc algoth s used fo efnng the ate odulaton esults wthn allowable ange defned wth the equaton (), (4), (0), and possbly wth less haonc bases usng ftness functon epesented wth equaton (). he choosoes fo the genetc algoth and the genetc opeatons ae shown n Fg. 6. In the Fg. 6, a choosoe s poposed to have ates of all behavos fo the least potzed behavo n the left to the ost potzed behavo n the ght, and thee ae 3 genetc opeatons fo next geneaton. Anyway wth any genetc opeaton, choosoes that volate the eal-te constants and choosoes that change poty ode fo the ate odulaton esults by the fuzzy contols ae not geneated though heustc adsson contols. Ftness = () Fg. 6. Choosoes and Genetc Opeatons Fg. 5. Coputatonal Resouce anage Value udgents have been studed fo goal acheveent n ntellgent systes(a.m.meystel and J.S.Albus, 2002). Values of behavos ae coputed by value udgent functons esdng n the eactve plannes. he value udgent echans can be defned wth equaton (9). Whee, e (,t ) s the value of th value vecto at te t, s (,t ) s the state of the th state vecto at te t, w (, ) s weght, that defnes the contbuton of s ( ) to e ( ), and k s a coeffcent that defnes the potance of devaton n the value udgent. 5. SIMULAION ESS In the followng sulaton tests, the autonoous oble obot should avod obstacles and each a taget, concuently wth tansttng gatheed envonental nfoaton to ts eotely located aste by weless councaton. e popetes of behavo sets and essage sets fo the sulaton tests ae shown n able. Fo the obstacle avodance, the B behavo n the ban odule tansts contol data to the M behavo n the oble odule though the CAN essage. And the B6 behavo n the ban odule pefos the functon of the envonental nfoaton

5 tanssson. In ths pape, only the ate of the behavo B and B6 ae odulated accodng to the poposed ate odulaton stategy fo the splcty of the sulaton tests. d e( t + dt ) = (7 + )(000 s( t )) dt (2) ( f e( t + dt ) 0,e( t + dt ) = 0 ) Ban Module Moble Module CAN Message able. e Popetes of Behavo Set and Message Set fo Sulaton est Behavo C [S] [S] [S] B B B B B B Behavo C [S] [S] [S] M M M M M Message Sze [Byte] [S] CAN CAN CAN CAN CAN consdeed as fuzzy nput. In the equaton (2), s(t) s a sensoy nput that epesents the nu dstance n centete to suoundng obstacles. he sensoy nput s calculated n a ultple channel ultasonc senso odule. Input ebeshp functons and output ebeshp functons fo the fuzzy contol ae shown n Fg. 7 and Fg. 8. Sple nfeence ules fo the fuzzy contol ae sae as followng: () If the value s 250, the ate of the obstacle avodance s odulated by 2.0 tes, and the ate of the nfoaton tanssson s odulated by 0.5 tes. (2) If the value s 500, the ate of the obstacle avodance s odulated by.0 te, and the ate of the nfoaton tanssson s odulated by.0 te. (3) If the value s 000,the ate of the obstacle avodance s odulated by 0.5 tes, and the ate of the nfoaton tanssson s odulated by 2.0 tes. Fg. 9. Sulaton Envonents Fg. 7. Input Mebeshp Functons ests ae pefoed on sulated envonents shown n Fg. 9. As shown n the Fg. 9, the obot has 5 ultasonc sensos and the sze of a gd s 30 squae centetes. he sze of the obot s also 30 squae centetes. Because the obot fo the sulaton tests s equpped wth ultasonc sensos, sensoy nputs of the nu dstance to obstacles ae odelled wth Gaussan pobablty dstbuton n the test(boensten J. and Koen Y., 99). Fo efnng ate odulaton though the genetc algoth, the populaton sze of the one-geneaton s 00, and total 00 geneatons ae ceated fo a choosoe wth the best ftness value. Fg. 8. Output Mebeshp Functons Fo the ate odulaton contol, the fuzzy contol wth one nput and one output s pleented. In the fuzzy contol, value calculated by equaton (2) s Fg. 0. Behavo-to-Behavo Response e

6 In Fg. 0, the behavo-to-behavo esponse te of essage tanssson fo the B to the M though the CAN wth the poposed coodnated schedulng stategy s copaed to behavo-to-behavo esponse te of t wthout the poposed stategy. As shown n the Fg. 0, the aveage of the behavo-tobehavo esponse te wth the poposed stategy s 568S, whle the aveage of the behavo-tobehavo esponse te of t wthout the poposed stategy s 965S. he esponse te wth the coodnated schedulng s educed by about 40%. Fg.. Bandwdth Utlzaton of B6 In Fg., the bandwdth utlzaton of the B6 wth the poposed ate odulaton of the B and the B6 s copaed to bandwdth utlzaton of t wthout the odulaton stategy. he bandwdth utlzaton of the B6 wth the poposed ate odulaton s hghe than the constant bandwdth utlzaton of the B6 wthout the poposed ate odulaton n ost te. he bandwdth utlzaton of the B6 wth the poposed ate odulaton s lowe than the bandwdth utlzaton of the B6 wthout the poposed ate odulaton fo a oent when the obot eet naow path. 5. CONCLUSIONS In ths pape, effcent esouce schedulng stateges fo a netwok-based autonoous oble obot wth hybd obot contol achtectue ae poposed. he schedulng stateges ae fo the nzaton of behavo-to-behavo delays when behavos councate wth othes ove netwok, and fo the optal usage of coputatonal esouce on each netwok node of the obot. he bass of the esouce schedulng stateges s the DMS. In ths pape, soft deadlne and had deadlne ae newly defned wt the DMS, the soft deadlnes of behavos o essages ae odulated though coodnated schedulng stategy fo the nzaton of the behavo-tobehavo delays. he coodnated schedulng stategy confgues the soft deadlnes consdeng poceedng constants. A odulaton stategy of the had deadlnes-ates s also poposed n ths pape fo the optal usage of coputatonal esouce. he odulaton s pefoed based on the dynacal values of the behavos unnng on an opeatng syste n each node. o copensate the uncetanty of the dynacal values nfeed by senso nfoaton, the fuzzy contols ae used fo the odulaton, and the genetc algoth s also used to efne the ate odulaton esult consdeng optal eal-te feasblty. hough sulaton tests, schedulng esults wth the poposed stateges ae copaed wth esults wthout the poposed stateges to vefy the pefoance enhanceent by the poposed stateges. Fo the sulaton test, t s vefed that the behavo-to-behavo esponse te wth the poposed coodnated stategy s educed fo the esponse te wthout the stategy. And t s also shown that the utlzaton bandwdth can be nceased wth the poposed ate odulaton stategy REFERENCES A.M.Meystel and J.S.Albus, "Intellgent Systes Achtectue, Desgn and Contol", Wley Intescence, 2002 Boensten J. and Koen Y., "he Vecto Feld Hstoga - Fast Obstacle Avodance fo Moble Robots", IEEE ans. Robotcs and Autoaton, 7(3), pp , 99 Dukn Pae, Hongyeol K, Daewon K, Hongseok K, "affc Analyss of A Netwokbased Contol Syste Usng the CAN", 2002 Congess of IFAC, July 2002 Hongyeol K, Daewon K, HongSeok K, and Hogl Lee, "owad the Pesonal Robot Softwae Faewok", ICCAS Conf., pp , 2002 Hongyeol K, Daewon K, Hongseong Pak, HongSeok K, and Hogl Lee, "Robot Softwae Faewok n open dstbuted achtectue", Koea Doestc Patent, 2004 KIECH, "Study on Syste Engneeng echnology fo Pesonal Robots", echncal Repot, 2004 K.J.Asto and B.Wttenak, "Copute- Contolled Systes", Pentce Hall, 997 K.M.Zube and K.G.Shn, "Schedulng Message on Contolle Aea Netwok fo Real-e CIM Applcatons", IEEE ans. on Robotcs and Autaton, vol. 3, n. 2, pp , Ap. 997 Mavo D and Natale M., "Schedulng the CAN bus wth ealest deadlne technques", Poceedngs, he 2st IEEE Real-e Syposu, pp , Nov N.C.Audsley, A.Buns, and M.F.Rchadson, "Had Real-e Schedulng: he Deadlne Monotonc Appoach", Poc. of IEEE Wokshop on Real-e Opeatng systes and Softwae, 99 R.Ala, R.Chatla, S.Fleuy, M.Ghallab, F.Ingand, "An Achtectue fo Autonoy", Intenatonal Jounal of Robotcs Reseach, Vol. 7, pp , 998 Robet Bosch GbH, "CAN Specfcaton Veson 2.0", 99 R.C.Akn,.Balch, "AURA: Pncples and Pactce n Revew", Jounal of Expeental and heoetcal Atfcal Intellgence, pp.75-89, 997.W.Kuo and A.K.Mok, "Inceental Reconfguaton and Load Adustent n Adaptve Real-e Systes", IEEE ans. on Coputes, Volue 46, Nube 2, pp , 997