Automated Guided Vehicle Control System for Territorially Stationed Flexible Manufactures

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AUTOMATED GUIDED VEHICLE CONTROL SYSTEM FOR TERRITORIALL Y STATIONED FLEXIBLE MANUFACTURES V. A. Veselov, V. G. Kuznetsov, V. K. Mishkinyuk, V. P. Noskov, L. N. Polyakov and P. S. Sologub Ll'lli ll!imr/ . L'SSR

Abstract. 'r his paper describe s the main units of the automateu guided vehiclF control system. They are the vehicle vision unit and appropriate control unit which arE' to provide for automat ed selectio:1 of optimal vehicle path as well a s traffic safety takin:>; account of chan~e­ able traffic si tUB. t i<' ~ ~ . '{eyw::>r,L3. yehicles

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I ITTft0Dl:Cn H Assembly ant "l'H-.' .i. "·' ,.,' territ o "iy,I. ' .y stationed fl=xi b.1.~ manuf~ctures is to provide for fl e xible ne t wo rk of load and part :~ trans po rtat J."Ji. between the manufactures. The netv/Ork can be implement e :l on the basis of usual ~oad network and some automated ~ided vehicles )quip ped 'n i th vehicle vision and appropriate control units. The on-board and real-time working vehicl e vision and control units are to provide for plannin g the o ptimal path from vehicle current positior. to the closest target as well as traffic safety. rHE '{EHIGLE VISI Oa UNIT

The vehicle vision unit is to measure the envi.ronment geometric parameters directly. It is ShC Vlfl i 'l ?i ,~ . 1 and contains laser rang e finder (1), scanning unit (2), memor ,'f unit and c oordinat e convertor (3 ) . The ran .~e finder is made on the basis of the low- powered ( 1J ;n'N) semic 0:id.uctor laser. It operates in the closest (O, 9;um) infrared spectrum. The laser range finder provides for the distWlce measurement in the ranse of 0 , 2 - 20 f!) . wit h t -'l e error bein.><: about + J ,05 m. The main part of the scannin ,~ unit is the movable laser beam deflectil19; mirror p ossessin ~ two additional degrees of freedom cl. and J3 (Fi .~. 2). 'r hey are controlled by means of d.c. electric motors. The program of scnnnin~ is set into the memory lli.it and may be chrulged. The vision seator is 120 0 in azimuth and 45° in eminence. The view discreteness is 1.5°. Thus, the environment coordinates measurement is direct ~l d takes plac~ i n th~ spher~cal coord~llat e system ~ 01, d.,J3 ) w~th its ctl::J.tre positioned in the mirror suspension point. The latter i s displaced relative to the vehicle coordinate system ( 0 Xl Yj Z , ) by the vector ' The frequency of coordinates measurement

is about 5 kHz. The enviro'lmen t is viewed frwne by frame. Time taken to have one frame is about 0,75 s. COORDL'lATE COlI'lERTOR

The measured environment parameters ( dId, ~ >, the vehic le an ~ les about the longiiudinal and transverse axis (~, tJ- ), the course angle 'f and current vehicle coordinates < XOJJ YQU ~l >are set into the coordinate convertor. The latter determines t he environment point coordinates i n the cartesian coordinates ( 0 Xo ':10 Z y ) with re ~ard to the mechanical diagram in Fi g . 2. Thus, the convertor makes the f o llowing;

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The convertor is one-board special processor on the basis of 131 cellular circuits with flexible structure. It takes about 50f1 s t o make one convex'sion. THE RECOG:,ITIO:{ m IlT

The calculated coordinates of one frame pointa of environment are set into the recognition unit memory . The latter is to classify the environment surface with obstacles on it into the set of areas permitted or forbidden for vehicle motion. The obstacles are buildings. other vehicles, road rou .~hness and so on. In or der to simplify the procedure of the environment surface classificRtion the followin ~ algorithm based on the profile cross-country capability characteristic ( PC ) is suggested. The PC is known for each vehicle and determined by vehicle mechanism charaoteristics such as its wheel diameter and clearanoe as well as

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and determined by vehicle mechanism characteristics such as its wheel diameter and clearance as well as limitations in driving motor characteristics and in surface grip of a wheel. In case of driving along the rough road the PC is IJZm=/(t?) Here .1 Zm - the critical hight differen.:' ce of two any points of the road, 2 - horizontal projecc:: VLl. X2 -I- LlYo tion of ctosen pair points distance. Value t ~ L - the vehicle bHs e . The typical PC is shown in Fig. 3. Here D~m = ~o by t=O and corresponds the step hight which vehicle can overcome. On the other hand em- is the critical angle the vehicle Cfl.!l overcome. The availability of the vehiclp PC and the data array of the surface point coordinates provides for the followin .~ environment modellin,o; algori tlull . The pairs of the measured surface points are selected. They are to havt' t t Then for each pa ir the hi .o;ht difference Ll Co is determined and compared to Ll Zm =j (t) The discrete environme!1t surface areas having even one point with hight Ll Z o ~ LJL!m are supposed to be forbidden for vehicle motion. The addresses of the above areas are determined by coordinates Xo , Yo of the corresponding points having Ll Z:u ~ L1 Zm In this way all of the environment surface areas ..are examined. It is done in all possible directions.

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The above algorithm of envirorunEont surface classification is s i nlple. It allows to use all of the visual information and to process it in parallel comparing some pairs point coordinates at the same time. Thus, it is possible to implement the onboard real-time recognition unit. The above algo ri tI'm., by the way, may be used to classify the rou,y'1 surface in sense of motion difficul tiN! in more detail. For this purpose it is necessary to have a set of the PC's each of them being constructed. for definite surface roughness beine; passed. The rec o.:>;1i ti of'. unit has been implemented on the above LSI cellular circuits. The vehicle vision uni t, the convertor and the reco,o;ni tion unit compose the vehicle vlsion system ( Fig. 4). CONTROL UNIT Thus, there if! a two-dimensional map of the three-dimensional environment in the control system memory unit. The map is a set of discret e areas permi ttell or forbidden for motion. The control unit plans the optimal path from vehiclf> current position to the closest target on the map. The unit ensures the obstacles avoidance, riding over or atop. The path is built with regard for vehicle width. The optimal path is determined. by wave algorithm. This control unit is on-board and realtime working . It has been implemented on the same LSI celllllnr circuits. CONCLUSION The laser vehicle vision system, the oontrol unit implemented on the base of the flexible LSI cellular circuits and the above simple algorithm allowed to oreate the on-board real-time vehiole control system providine for safety vehicle guiding with the speed up to 10 km/h.

REFERENCES Kalyaev, A.V., V.P.Noskov, Y.V.Chernuchin. (1980). The algorithm of the vehicle control structure. I. AN USSR. Technitcheskaya kibernetica, N4. Moscow, pp.64-72 (in Russian). Kemurdjan A.L., V.A.Veselov, Y.M.Kozlov, P.S.Sologub. (1985). Adaptation in the transport robots. I. AN USSR. Kibernetic questions. Adaptive control theory and practic problems. Nauka. Mosoow. pp.106-116. Ohozimsky D.E., A.K.Platonov, V.A.Veselov, V.G.Kuznetsov, y.L.BessonovjN.p.Chernousov, I.V.Yashumov. (1981 • Technical vision systems on the basis of the semiconduct or lasers. Sb.trudov The problems of the machine vision in robots. Moscow, LP.M. AN USSR, pp.10

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Chernuchin Y.V., V.P.Noskov, I.A.Kalyaev, L.J.Us6chyov, V.K.Mishkinyuk. P.S.Sologub (1984). The transport robot mio roprocessor oontrol system. Microprozessornie sredstva i sistemy, In, pp.70-72 (in Russian).

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Fig. 4. Functi onal dia~ram of the robot vision system Fig. 2. Kinem atic diagram of the laser vision system and coordi nate system s being used