Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article

Transcription

1 Avilble online Journl of Chemicl nd Phrmceuticl Reserch, 04, 6(5):90-95 Reserch Article ISSN : CODEN(USA) : JCPRC5 Anlytic hierrchy process to tennis bll-picking robot different pth progrmming reserch Fng Peng Trining Deprtment, Shenyng Sports University, Shenyng, Lioning, Chin ABSTRACT Tennis bll-picking robot is vrious in kind; bll-picking wy minly divides into recircultion principle, proximity principle nd shortest pth optimiztion principle such three kinds. At present, world developed chievements cn let robot to pick up rndom dispersion of tennis. The pper mkes use of nlytic hierrchy process, it nlyzes bll-picking robot different wlk pth tht is picking wy, by estblishing hierrchicl nlysis indictors, it reserches on bll-picking robot pths differences cused influences, nd mkes preliminry theoreticl bsis for pth reserching directions. Finl result thought tht shortest pth optimiztion principle hs more prcticl significnce in reserching significnce nd development prospect. Key words: tennis robot, nlytic hierrchy process, pth, comprehensive evlution INTRODUCTION In the erly 980s, world firstly put forwrd proposl of orgnizing tble tennis robot competition, fter tht ll countries in the world strted sports kind robot reserching; sports robot included competitive sports robot nd service type sports robot [-5]. Service type robot will ply n importnt role in sports in the future. Sports robot will lso more rpidly blend in with people dily life s exercising. Low cost, high efficiency, brod prospects re pplied vlues of robot [6-9]. Tennis constntly wlks into people s life, more nd more people prticipte in tennis, tble tennis nd other bll type events, nd with movement generted scttering blls spred ll field corners, bll picking becomes kind of trivil nd unvoidble thing [0-5]. So in order to solve the problem, bll-picking robot becomes idel service tool. Formers hve mde lots of reserches on bll-picking robot development spect, especilly for mthemticl model spect model clcultes nd controls equtions s well s other mthemticl lgorithms reserch. But bll-picking robot designing is kind of very complicted tsk tht includes mchinery, utomtion, computer, mthemticl model, physicl model nd control eqution so on multiple disciplines, is n interdisciplinry reserch field. The pper bsed on nlytic hierrchy process, strts from bll-picking robot pth perspective, it nlyzes nd reserches on bll-picking pth reserch orienttion. BALL-PICKING ROBOT INDICATOR ANALYSES Investment costs Picking robot performnce Investment costs is one of key fctors tht considers introducing bll-picking robot, excessive high investment costs will led to pth reserch lose more thn gin, so tht it will restrict bll-picking robot development. Different pths robot, due to its control methods nd reltive ssisting equipments differences, it will led to investment costs differences, low investment costs is common trget mong resercher, mnufcturer nd demnder. Therefore robot investment costs re kind of importnt indictors in pth selection reserching problems. 90

2 Fng Peng J. Chem. Phrm. Res., 04, 6(5):90-95 Picking efficiency Robot should reflect its utility, people s expecttion on bll-picking robot of course is it cn mke self-service to pick up scttering blls nd cn mke self-service nd pick up nerly ll blls. Tht reflects picking efficiency indictor requirements on bll-picking robot, nd in different wys bll-picking pths, compre their efficiency differences re indispensble. Reserch Significnce Different picking pths reserch corresponding reserch in other expnsion spects re different, nd they hve different impcts on eduction, design, science nd technology, economic spects. Such reserch hs more universlity, nd cn more drive other reserches dvncement tht is the key to reserch significnce. When evlutes bll-picking robot pth reserching methods, reserch significnce is n importnt reference indictor. Stbility In tennis, tble tennis nd other events, bll dispersion is rndom nd quntity is lrger, is unremitting drop blls picking. Robot work is lrger nd menwhile it requires robot work time to be longer. It requires robot hs better stbility so tht let robot crry out trying stble work in whole movement. ANALYTIC HIERARCHY PROCESS MATHEMATICAL MODEL ESTABLISHMENTS Estblish hierrchicl structure The pper quntize tennis bll-picking robot bsed on nlytic hierrchy process. It estblishes trget lyer, criterion lyer nd project lyer reltions. Trget lyer: bll-picking robot property. Criterion lyer: project influence fctor, c is investment costs c c is picking efficiency is stbility is mnufcturing difficulty. A Project lyer: is recircultion A is proximity principle, A is optimiztion principle obtined hierrchicl structure. Construct judgment mtrix Bsed on Tble showed ~9 scle tble, it mkes weight nlysis. Tble :~9 scle Scle ij Description fctor i nd fctor j hve equl importnce fctor i is slightly more importnt thn fctor j 5 fctor i is reltive more importnt thn fctor j 7 fctor i is extremely more importnt thn fctor j 9 fctor i is bsolute more importnt thn fctor j,,, Indictes middle stte corresponding scle vlue of bove judgments Reciprocl If compre fctor i with fctor j, it gets judgment vlue s ji =/ ij, ii = At first solve judgment mtrix, ccording to bove principle, reference ~9 scle setting, nd ccording to expert nd uthor s experiences s well s reference lots of documents, it gets pired comprison mtrix tht re respectively Tble -4. Tble : Comprison mtrix G c c c c / c /8 5 5 c / /5 / /5 9

3 Fng Peng J. Chem. Phrm. Res., 04, 6(5):90-95 Tble : Comprison mtrix c A A A c A A A A / A 5 5 A / A A /5 5 A /5 /5 Tble 4: Comprison mtrix c A A A A A A A 5 8 A 5 8 A /5 5 A /8 /5 A /5 5 A /8 /5 Hierrchicl single rrngement nd consistency test Use consistency indictor to test: Set in comprison mtrix, is imum feture root vlue, n is comprison mtrix order: n CI n CI vlue gets smller; judgment mtrix gets closer to completely consistent. CI vlue gets bigger, it shows known extent is lower. Hierrchy totl rrngement nd its consistency test / 5 5 A / / 5 / / By column vector normliztion Solve sum by line =W Normliztion / AW / / / / w Similrly, it cn clculte judgment mtrix: 9

4 Fng Peng J. Chem. Phrm. Res., 04, 6(5):90-95 / B /, B / 5, B / 5 5, B4 / / 5 / 5 / 8 / 5 / 8 / 5 Therefore, it gets imum feture vlue nd feture vector s following show: 0.54 () ().64, () ().0, () ()., (4) ().98, n CI CI CR Use consistency indictor to test: n, RI, RI vlue is s Tble 5 show. Tble 5: RI vlue n RI It gets judgment mtrix A, 4.07, RI CI CI 0.04 CR RI 0.90 It represents A inconsistency test is effective nd it moves in permissible rnge, it cn use A feture vector to replce weight vector. B Similrly, to judgment mtrix B,, B B, 4, it tkes consistency test nd gets weight vector. Utilize hierrchicl chrt drwing out clcultion results from trget lyer to project lyer, s Figure show. Figure : Trget lyer to project lyer structurl chrt 9

5 Fng Peng J. Chem. Phrm. Res., 04, 6(5):90-95 Clcultion structure s following: () () () () () (,,, ) = () w w w MODEL IMPROVEMENTS Proximity principle is different from other ny pths, it puts emphsis on nlysis from its own surrounding perspective of every bll distnce in the field to mke nlysis nd solve shortest pth. But in cse bll quntity is little or reltive scttering, compred to optimiztion movement, its weight is smller. Estblish hierrchicl structure s Figure show. Figure : Improved trget lyer to project lyer hierrchicl structurl chrt Clcultion structure s following: () () () () () (,,, 4 ) = () w w w By result nlysis, recircultion ccounts for 56.% of investment costs, nd optimiztion only ccounts for 4.4%, proximity principle ccounts for 8% of reserch significnce, nd optimiztion principle ccounts for 54.%, the pper concludes tht bll-picking robot is kind of lrger weight reserch in reserch significnce spect. CONCLUSION The pper utilizes nlytic hierrchy process, dopts different pths to reserch on bll-picking robot, it cn define tht dopts optimiztion lgorithm cn propel to robot development, improve reserch process, nd it belongs to reserch items tht should strive to develop. And proximity principle nd recircultion pth hve lower investment 94

6 Fng Peng J. Chem. Phrm. Res., 04, 6(5):90-95 costs, but technicl synthesis nd overll evlution is lower thn optimiztion pth lgorithm. REFERENCES []Alirez Fdei Tehrni, Ali Mohmmd Doosthosseini, Hmid Rez Mobllegh, Peimn Amini, Mohmmd Mehdi DneshPnh. RoboCup, 00, [] R.E.Klmn. Trnsction of the ASME - Journl of Bsic Engineering,960, ( 8), [] Crlos F. Mrques, Pedro U. Lim. RoboCup, 000, [4] S.Thrun, D.Fox, W.Burgrd, nd F.Dellert. Artificil Intelligence Journl, 00, (8), [5] KAN Li-ping. Bulletin of Sport Science & Technology, 0, 9(),9-0. [6] Zheng Wei. Sport Science nd Technology, 000, (), -6,. [7] Yng Jilin et l. Journl of Shndong Physicl Eduction Institute, 00, 8(),5-5. [8] WANG Xin. Journl of Nnjing Institute of Physicl Eduction, 00, 6(5), [9] ZHANG Ji, xing. Journl of Hubei Sports Science, 00, (),74-75, 79. [0] Li Ning, Zhou Jindong. Journl of Jilin Institute of Physicl Eduction, 0, 7(): [] Xiomin Zhng. Journl of Chemicl nd Phrmceuticl Reserch, 0, 5(), 8-4. [] Wng Bo; Zho Yulin. Journl of Chemicl nd Phrmceuticl Reserch, 0, 5(), -6. [] Mingming Guo. Journl of Chemicl nd Phrmceuticl Reserch, 0, 5(), [4] Bing Zhng; Zhng S.; Lu G.. Journl of Chemicl nd Phrmceuticl Reserch, 0, 5(9), [5] Bing Zhng. Journl of Chemicl nd Phrmceuticl Reserch, 04, 5(),