A Method to Estimate Ball s State of Spin by Image Processing for Improving Strategies in the RoboCup Small-Size-Robot League

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A Mtho to Estimat Ball s Stat of Spin by Imag Procssing for Improving Stratgis in th RoboCup Small-Siz-Robot Lagu Yuji Nunom, Kazuhito Murakami, Masahi Ito, Kunikazu Kobayashi an Taashi Narus Grauat School of Information Scinc an Tchnology, Aichi Prfctural Univrsity, Nagakut, Aichi, 480-1198 JAPAN School of Information Scinc an Tchnology, Aichi Prfctural Univrsity, Nagakut, Aichi, 480-1198 JAPAN : im132007@cis.aichi-pu.ac.jp, : {murakami, masa-ito, kobayashi, narus}@ist.aichi-pu.ac.jp Abstract. This papr arsss an stimation problm of th ball s stat of spin in RoboCup Small Siz Lagu (SSL). A spinning ball varis its sp aftr th ball bouncs off th floor. This papr proposs an imag-bas stimation mtho of th ball s stat of spin, in particular, by using inrtia fatur of co-occurrnc matrix of th imag squnc. Th ffctivnss of our propos mtho is shown by som xprimnts. 1 Introuction Th RoboCup small siz lagu (SSL) is on of th soccr lagus in th RoboCup [1][2]. Th siz of robot is limit lss than 180mm iamtr an lss than 150mm hight. Each tam which consists of six robots plays th gam on a fil of siz 8090mm 6050mm. Four camras ar quipp abov th fil to ovrlook th ntir fil. Th positions of th robots an th ball ar rcogniz by th imag. Bas on th position information, ach tam cis an appropriat stratgy. Each robot can kick th ball in two iffrnt ways, straight-kick-typ an loop-kick-typ (call chip-kick), an also has a rolling mchanism which givs a strong spin to th ball. Whn th ball is chip-kick with strong spin, th spinning ball varis its sp aftr th ball bounc off th floor. This maks it ifficult to prict th locus of th ball. So, th stimation of th ball s stat of spin is vry important to ominat th gam. Fw papr has bn rport in th fil of stimating ball s stat of spin in th RoboCup SSL. In som ball gams, svral paprs hav bn rport to stimat it by high-sp camra. Inou t.al rport how to stimat th vctor of spin axis an sp by tracing a sam pattrn on th surfac of th ball by using a high sp camra [3]. Thy obtain th rotation axis an spinning sp by comparing th input imag with th imag stor in atabas. Tamaki t.al rport a mtho to stimat spinning sp by imag rgistration [4]. Thy utiliz an information of th mark on th surfac of th ball. Liu t.al

propos a mtho by using two high sp camras to calculat both of ball s sp an spinning sp [5]. Ths mthos coul b appli if som kins of mark pattrns ar attach or print on th surfac of th ball. In Robocup SSL, a golf ball is us, so it is ifficult to apply ths imag procssing mthos straightly bcaus thr is no fatur on th surfac of th golf ball xcpt makr logotyp. An furthrmor it is not so asy to st up an control xpnsiv multipl high sp camras. Frico t.al rport how to stimat rotation of th ball without using high sp camra [6]. In thir mtho, th vctor of spin axis an sp ar stimat by using th movmnt of th six marks that ar plac on th surfac of th soccr ball. Howvr, thir mtho coul b us unr th conition that th rotation sp of th soccr ball is 10 rps or lss. In th RoboCup SSL, th rotation sp is vry high (mor than 30rps), so it is ifficult to apply this mtho. Whn a ball is spinning, som kin of blur is obsrv in th rgion of th ball. On of th principal factors of blur is th impls on th surfac of th ball. Th gr of blur changs accoring to th xposur tim of th camra an th rotational sp of th ball. This papr proposs a nw mtho to stimat th ball s stat of spin by using inrtia fatur of co-occurrnc matrix of th imag squnc. This mtho osn t n a spcial pattrn attach on th surfac of th ball. In this papr, sction 2 scribs our basic ia to stimat ball s stat of spin an sction 3 xplains concrt mthos to calculat inrtia fatur an co-occurrnc matrix an sction 4 xprsss xprimntal rsults to show th ffctivnss of th propos mtho, an aftr that, sction 5 iscusss th rotation sp of th ball an application to stratgy. 2 Basic Ia In th RoboCup SSL, an orang golf ball is officially us. Thr ar many impls on th surfac of th ball. Ths impls caus th changs of rflction an this rflction changs accoring to th gr of blur. Figur 1 shows th iffrncs of th imags. Fig. 1(a) is a static ball s imag an som highlight rgions xist in it, on th othr han Fig. 1(b) is a spinning ball s imag an it looks lik a smooth imag. It will b possibl to stimat th ball s stat of spin by analyzing th istribution of rflction. In orr to obsrv th surfac of th ball, lt an aitional camra (i.. PTZ camra) b install to th vision systm as shown in Fig. 2. Th ata flow of our vision systm is shown in Fig. 3. In th RoboCup SSL, th stanar vision systm call SSL-Vision [5] is utiliz an it sns th information of th position an ID of ach robot an th ball. In aition to ths information, to sn th ball s stat of spin ralizs a nw stratgy to cop with an irrgular bounc of ball.

(a) static ball (b) spinning ball Fig. 1: Diffrncs of th imags Fig. 2: Camras layout Fig. 3: Data flow of vision systm

3 Imag Procssing Mtho to Estimat Ball s Stat of Spin Th main flow of our imag procssing systm is shown in Fig. 4. Our systm is compos of 3 parts of imag procssing. First, th ball s rgion is xtract (Stp1), thn co-occurrnc matrix an inrtia fatur ar calculat in th ball s rgion (Stp2), an finally th ball s stat of spin is stimat (Stp3). Dtails of ach stp is as follows: Stp1. Extraction of ball s rgion Lt ach fram of imag squncs b inputt. An xampl of input imag is shown in Fig. 5. Thn, mak th grayscal imag that is high valu in th ball rgion (Fig. 6) an th grayscal imag is thrshol by iscriminant analysis mtho. Thrshol imag is procss by xpansion an contraction, thn, thrshol imag is labll. Aftr th imag is labll, lt th scon largst rgion b that of th ball (Fig. 7). Thn, xtract th rctangl rgion that of th ball s rgion. In th rctangl rgion, covrt to (R,G,B)=(0,0,0) xcpt ball rgion. Thn, lt th rctangl rgion as shown in Fig. 8 b th procssing rgion in th following procsss. Input imag Thrsholing for color spac Lablling Extraction of ball s rgion Caluculation of co-occurrnc matrix Caluculation of inrtia fatur Thrsholing Jugmnt of ball s stat of spin Fig. 4: Flowchart of imag procssing

Stp2. Calculation of co-ocurrnc matrix an inrtia fatur First, calculat co-ocurrnc matrix P δ (i, j) from th B-channl imag of th xtract rgion in stp1. Hr, Dx an Dy b th iffrncs of x- an y- coorinats of two pixls, rspctivly, an δ = (D X, D Y ) nots th vctor of thm, an i an j ar th valus of ths two pixls. Th inrtia fatur In is calculat from P δ (i, j) as In = n 1 i=0 n 1 j=0 (i j)2 P δ (i, j) (1) Stp3. Jugmnt of ball s stat of spin For ach fram, th intrtia fatur In is thrshol by an suitabl valu an th ball s stat of spin is jug as follows: StaticStat (In > T hrshol1) BallStat = U nknowstat (T hrshol2 In T hrshol1) SpinningStat (In < T hrshol2) Fig. 5: Original imag Fig. 6: Grayscal imag Fig. 7: Ball s rgion**** **** Fig. 8: Enlarg imag to b procss T hrshol1 an T hrshol2 ar asily obtain, for xampl, by iscriminant analysis, bcaus th valu of fatur In ar gratly iffrnt. U nknowstat is th transition btwn StaticStat an SpinningStat.

Static Stat Thrshol1 Spinning Stat Thrshol2 valu of fatur In fram numbr of imag squnc (a) Th changs of th inrtia fatur 0 200 400 600 800 1000 1200 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 f r q u n c y valu of fatur In (b) Distribution of frquncy (c) Avrag an stanar viation of In in ach stat StaticStat SpinnningStat Av. 44.978 9.201 S.D. 3.177 1.124 Fig. 9: An xampl of th th inrtia fatur for an imag squnc (spin an stop is rpat)

4 Exprimnt Figur. 9(a) shows an xampl of th changs of th inrtia fatur for an imag squnc in which th ball rpats spinning an stopping. It is known from th figur that In is chang largly btwn th ball s stat is spinning an stopping. Figur. 9(b) shows frquncy of fatur In an Tab. 9(c) shows avrag an stanar viation of In in StaticStat an SpinningStat. Spinning an stopping imags ar takn by A601fc (Baslar mak) [6] an th paramtrs of th camra ar as follows: -fram siz: 656 490 pixls -fram rat: 30 FPS -xposur tim: 1/60 scons Th prformanc of our propos mtho is valuat by calculating succss rat. Th ball s stat was stimat by propos mtho, whr T hrshol1 = 35 an T hrshol2 = 13. Lt BS n an BS n b th ball s stat in th n-th fram by imag procssing an its truth, rspctivly. SUCEESS or F AILURE was givn by if ((BS n == StaticStat)&&(BS n == StaticStat)) SU CCESS ls if((bs n == SpinningStat)&&(BS n == SpinninngStat)) ls SU CCESS F AILURE 6054 of 6100 frams succ, thus th succss rat in this cas was about 99.2%. 5 Discussions 5.1 Rlation btwn inrtia fatur an rotation sp In orr to obtain th rlation btwn th valu of In an th spinning sp, w xprimnt by changing th rotation sp of th ball. Th rsult of th inrtia fatur for th rotation sp is shown in Fig. 10. It is shown from Fig. 10 that th valu of inrtia fatur In crass accoring to th incras of th spinning sp of th ball, so it will b possibl to stimat th spinning sp of th ball if this curv coul b mol by som xprimnts at th vnu of th comptition [9]. 5.2 Rlation btwn rotation sp an ball s trac aftr th ball bounc off th floor It will b possibl to prict th ball s movmnt by stimating th rotation sp of th ball. Fig. 11 shows th trajctory simulations that th ball is kick

n 7 6.5 6 I 5.5 r u 5 t a 4.5 f f o 4 u l 3.5 a v 3 2.5 0 5 10 15 20 25 30 35 rotational sp(rps) Fig. 10: An xampl of th changs of th inrtia fatur for an imag squnc (spin an stop is rpat) at 5m/s an 60 grs with iffrnt rotation sp. In th cas of StaticStat, th kick ball is trac as shown in Fig. 11(a) an rachs to 4m istanc. In th cas of 10rps rotation sp, th kick ball is mov as shown in Fig. 11(b). In th cas of 20rps rotation sp, th kick ball is com back by strong spin as shown in Fig. 11(c). Th spinning ball varis its sp aftr th ball boun off th floor. Thus if th rotation sp of th ball can b stimat, th trajctory of th ball aftr th boun off th floor will b prict mor accuratly. 5.3 Application to stratgis Th propos mtho scrib can b appli to various stratgis in th RoboCup SSL. Ovrviw of th application to our stratgis is shown in Fig. 12. It is possibl to apply th stratgis, if th trajctory of th ball can b prict. Nw fns stratgis will b possibl as shown in Fig. 13 (in this figur, th blu robots ar ours, th yllow ons ar opponnt robots). In th fns, th following situation is xpct: Figur 13 shows an xampl of a fns stratgy improv by th propos mtho. W hr suppos th following situation: 1. th yllow ID1 is going to kick th ball an th blu ID1 blocks th straightkick pass. 2. Th yllow ID3 is in th position whr th ball will com aftr chip-kick by th yllow ID1, 3. an th blu ID2 is in th position whr this robot can block th yllow ID3 as shown in Fig. 13(a).

1.2 1 ) 0.8 (m t h0.6 ig h0.4 0.2 0 1.2 1 ) 0.8 (m t h0.6 ig h0.4 0.2 0 1.2 1 ) 0.8 (m t h0.6 ig h0.4 0.2 0 0 2 4 6 flying istanc (m) (a) in th cas of 0rps 0 2 4 6 flying istanc (m) (b) in th cas of 10rps 0 2 4 flying istanc (m) 6 (c) in th cas of 20rps Fig. 11: Trajctory simulation with iffrnt rotational sp

In this situation, (Stp1) th ball s stat of spin is stimat by th propos mtho as shown in Fig. 13(a). Thn, (Stp2) th point of th ball bounc off th floor is stimat by Rojas s mtho [10] as shown in Fig. 13(b). Nxt, (Stp3) th trajctory of th ball aftr bounc is stimat as shown in Fig. 13(c), an finally (Stp4) vn if th yllow ID2 movs to th position of th ball aftr bounc, th blu ID2 robot is abl to mov to aroun th yllow ID2 robot for blocking shoot as shown in Fig. 13(). Accoringly, w can prvnt isavantagous situation. By stimating th rotation of th ball, it is possibl to corrspon to fns. Furthrmor, by stimating th rotation sp, it is possibl to improv th positions of robots for fns. Input imag Estimat ball s stat (propos mtho) Estimat trajctory of chip kick (Rojas s mtho) Estimat th point of th ball bounc (Rojas s mtho) Estimat trajctory of ball aftr ball bounc (4.1,4.2) Chang stratgis ynamically by using stimat information Fig. 12: Ovrviw of th application to stratgis

Block 3 Ball is Spinning! Ball bouncing position (a) Stp1: stimat th ball s stat (b) Stp2: stimat th position of th bounc ball Block!! Trajctory of th ball aftr bounc (c) Stp3: stimat th trajctory of th ball () Stp4: chang stratgy by using stimation Fig. 13: Application to stratgis (blu mark robots : our robots; yllow mark robots : opponnt robots) 6 Conclusion W hav propos a mtho to stimat th ball s stat of spin by using inrtia fatur of co-occurrnc matrix of th imag squnc. Th ffctivnss of our propos mtho was monstrat som xprimnts. W also iscuss th following things: 1) th possibility to stimat th spinning sp of th ball by th rlation btwn th valu of In an th spinning sp, an 2) an application to a fns stratgy of th RoboCup SSL. Th propos mtho works wll in our prototyp systm. In futur work, w n to confirm th robustnss in various nvironmnt. It is also important to implmnt our mtho to a stratgic larning systm. Rfrncs 1. About Robocup,http://www.robocup.org/about-robocup/, (20/6/2014 last accss) 2. Small Siz Robot Lagu - start, http://robocupssl.cp.ku.ac.th/, (20/6/2014 last accss) 3. Inou, T.,Umatsu, Y., Saito, H., stimation of Rotational Vlocity of Basball Using High-Sp Camra Movi, Th transactions of th Institut of Elctrical Enginrs of Japan. D, A publication of Inustry Applications Socity, Vol.131, No.4, pp.608-615 (2011). 4. Tamaki, T., Sugino, S.,Yamamoto, M., Masuring Ball Spin by Imag Rgistration, Procings of th 10th Kora-Japan Joint Workshop on Frontirs of Computr Vision : FCV 2004 pag.269-274 (2004)

5. Liu, C., Hayakawa, Y.,Nakasima, A., An On-Lin Algorithm for Masuring th Translational an Rotational Vlocitis of a Tabl Tnnis Ball, SICE Journal of Control, Masurmnt, an Systm Intgration, Volum 5, Issu 4, pp. 233-241 (2012). 6. F. Cristina, S. H. Dapoto, C. Russo, A lightwight mtho for computing ball spin in ral tim, Journal of Computr Scinc & Tchnology; vol. 7, no. 1, pp.34-38 7. Small Siz Robot Lagu - sslvision: http://robocupssl.cp.ku.ac.th/sslvision, (20/6/2014 last accss) 8. Baslr Inustrikamras - A600 Sris - A601fc: http://www.baslrwb.com/proucts/a600.html?mol=311, (20/6/2014 last accss) 9. Nunom, Y., Murakami, K., Kobayashi, K., Narus, T., A Mtho to Estimat Ball s Stat of Spin by Imag Procssing for Stratgic Larning in RoboCup Small-Siz-robot Lagu, Th Japans Socity for Artificial Intllignc,SIG- Challng-B301-4,pp.21-25 10. R. Rojas, M. Simon, O. Tnchio, Parabolic flight rconstruction from multipl imags from a singl camra in gnral position, RoboCup 2006: Robot Soccr Worl Cup X, LNAI vol.4434, pp.183-193