Active Compliant Motion Control for Grinding Robot

Transcription

1 Proeedings of the 17th World Congress The International Federation of Automati Control Ative Compliant Motion Control for Grinding Robot Juyi Park*, Soo Ho Kim* and Sungkwun Kim** *Daewoo Shipbuilding and Marine Engineering Co. Ltd., Seoul, Korea (Tel: ; **Korea Polytehni University, Siheung, Kyonggi-do, Korea (Tel: ; Abstrat: A grinding robot system is presented in this paper. Ative ompliant motion ontrol is applied to keep ontating between grinding tool and work piees and auto surfae traking algorithm was developed to trae the outline of work-piees. For real implementation of the system, the shape of work piees are informed through barode and the piee s dimension is measured with a laser distane sensor. Experimental results with the implemented system are also presented and disussions for further works are followed. 1. INTRODUCTION Grinding is one of the important proesses in Daewoo Shipbuilding and Marine Engineering Co. Ltd. (DSME) shipyard beause grinded omponents in ships help to extend life yle of ships. Sine ship-owners have been very satisfied with the ships that have well grinded omponents, they request to grind most parts for new ordered ships. The working environment of grinding proess, however, is very harmful to workers; Grinding noise is very large and dust is everywhere. Moreover, ontinuous vibrating fore auses workers musle-disease. A grinding robot system was, therefore, asked to develop to replae the workers in suh harmful environment. Although the grinding proess does not require highly skilled person, developing autonomous grinding robot system is very diffiult. Human workers easily ontrol ontating fore between grinder and work-piees and trak any unfamiliar surfae. However, fore ontrol and exat surfae traking is not easy ontrol problem for robot system. In ideal situation if we know the exat dimension and shape of workpiees, one an design the path of robot exatly. Work-piees in shipyard, however, have not good tolerane: normally the dimension is different up to few millimetres from CAD information and is not serious in ship building proess. Moreover, it s diffiult to plae work-piees at exat loation with exat orientation. Fore ontrol and auto surfae traking, therefore, are two essential tehniques in developing a grinding robot system. There are many useful algorithm and appliation example for the ontating fore ontrol. Hogan s impedane ontrol (1985) is one of the most famous fore ontrol algorithm. Chang et. al. (1995) developed a hybrid fore ontrol algorithm with time delay and applied it to two degree of freedom (DOF) robot to trak given surfae with desired fore. Kazerooni et. al. (1990,1991) proposed ative ompliant motion ontrol algorithm and suessfully applied it to diret drive robot. There are some result to develop robot system for grinding (Choi, 1999) and finishing (Wang, 2000) proess. Grinding fore ontrol in this work was developed based on ative ompliane ontrol. Auto surfae traking was performed by estimating tangential and normal diretion from the measured ontating and grinding fore. Shape of work-piees was informed by operator and dimension was measured with a laser distane sensor. The approahing position and diretion was alulated with the shape and dimension information. This paper organized in five setions. The next setion introdues grinding proess in shipyard, and grinding and traking algorithm is presented at Setion 3. Real implementation and experimental results are presented at setion 4 and the summary and disussion on further works are followed. 2. GRINDING PROCESS Grinding in DSME shipyard is a kind of mahining proess that removes materials with rotary utter having six blades. The grinding tool operates with ompressed air and nominal spindle speed is 6000 rpm. Sine the utter has six blades and rotates at 6000rpm, the utting fore vibrates at 600Hz. Grinding tool used in this work onsists of a utter, a guide plate and a guide roller (Fig. 1). As long as guide roller and plate keep ontating to work-piee, utter an ut workpiee to desired roundness. So, the ontrol strategy should be to ontrol the ontating fore that the guide roller and plate does not loose ontating. Sine suh strategy allows the ontating fore to exeed ommand fore, it is simpler than preise fore ontrol /08/$ IFAC / KR

2 industrial robot. It was proven that one an ontrol ontating fore with position or veloity ontrolled industrial robot position ontrolled type industrial robots (Roy, 2002, Surdilovi, 1996, Ferretti, 2000). Fig. 1. Shemati of grinding tool When human workers are working on this proess, the ontating fore is measured between 100N~200N and the feeding speed is about 100mm/s. Sine human workers usually repeat the grinding motion twie, averaging gridingspeed is regarded as 50mm/s. From the observation above, the ontrol strategy was determined as follows: - Maintain the ontating fore not to be below the minimum fore limit to keep ontating the guide roller and plate to the work-piee. - The ontating fore must not exeed the maximum fore limit to protet fore sensor and other mehanial parts. - Automatially trak the outline of work-piee based on the measured fore. In this work, about 200 types of work-piees exist and they an be ategorized in 24 shapes. Sine eah shape has speified grinding region as shown in Fig. 2, grinding system must know what the work-piees shape is in order to exatly grind the speified region. Sine the stiffness between work-piee and robot is very high, the slight robot movement auses large fore hange when robot is ontating work-piees; it makes diffiult to ontrol ontating fore with position ontrolled robots. To derease stiffness (or inrease ompliane), we imported an ative ompliane motion ontrol sheme (Kazerooni et. al, 1990, 1991). The blok diagram of the applied fore ontrol system is shown in Fig. 3. x d is the position ommand to the robot, K e is the natural stiffness between robot and work-piee. A ontroller is added to ontrol the ompliane of the losed loop, xr F. The ontrol law of ative ompliane ontroller is λh xd = ( kp + kds) xr F s + λ. (1) K P and H are ontrol parameters to determine the magnitude of the ompliane of the losed loop and K D is to inrease the stability of the system. Low pass filter is used to eliminate high frequeny noise and vibration omponent that is indued by the rotary girding utter. Fig. 3 Blok diagram of ative ompliane ontrol Sine the robot is the position ontrolled system the atual position, x, is follows the ommand position x d with some time delay. So, the dynamis of the robot, Gs (), an be simplified in (2), while it has unmodelled high order terms. Fig. 2 Examples of work-piees and grinding region to be grinded: dashed lines represent the grinding area a Gs () = s + a (2) The resultant ompliane of the losed loop, C CL expressed as, is 3. AUTOMATIC GRINDING CONTROL 3.1 Fore ontrol for grinding In the developed fore ontrol system, we used position ontrolled servo system and ontrolled the ontating fore by ontrolling the ommand position. While the most fore ontrol algorithm derived ontrol input as the terms of fore or torque of atuators, we used a position ontrolled xr 1 1 CCL = = + H = + H. (3) F K k G(0) K k e P e P So, we an get inreased C CL by inreasing H and dereasing K P. The maximum value of C CL, however, is limited in real system beause Gs () has high order dynamis and it is ativated when H beomes large. The optimal value of H annot be obtained analytially for the exat dynamis 4286

3 of Gs () is unknown. Instead, it was manually tuned by through series of experiments in this work. 3.2 Auto traking algorithm Basi idea of auto traking is to generate a motion ommand based on measured utting fore. Fig. 4 illustrates various fore and diretion while grinding work (Choo, 2006). Cutting fore, F, is measured from fore sensor and the diretion of utting fore,φ, is alulated from (5). where α0 and A0 are nominal values of α and A, respetively; k α and k A are onstant values, and 1 for x < 1 sat ( x) = 1 for x > 1. x otherwise Full blok diagram inluding auto-traing and ative ompliane ontrol is shown in Fig. 5. Fig. 4 Fore and moving diretion in grinding proess F = F (4) s ( Fy Fx ) φ = atan2,. (5) When the utting fore and diretion is obtained, the referene position ommand of (1), ( xr, y r), is alulated using following equation xr os( φ α) = A, (6) yr sin( φ α) where A and α are onstants number that are determined from desired traking speed and normal fore. Sine appreiate A and α are depends on the tools and workpiees ondition they should be tuned through trial and error in real system. An aeleration algorithm shown in (7) and (8) is added to inrease the grinding speed, where A and α are to replae those in (6). If the hanging rate of fore diretion, φ, is low it might mean striated surfae and the feeding speed is near maximum. Otherwise, rapid hange of measured fore means not striated surfae and the feed rate is dereased to keep ontating. φ α = α0 kα sat, (7) τφ s + 1 Fig. 5 Blok diagram of the auto-traking grinding fore ontrol system 4. IMPLEMENTATION OF GRIDING SYTEM 4.1 Implementation issues There are eight sub-tasks in grinding proess that we onerned in this work. Those are a. Bring a palette with work-piees to working area. A palette usually ontains 100 to 300 work-piees in one to six different shapes. b. Load a work-piee to the working plae.. Reognize the shape and size of work-piees. The edges to be grinded are speified is worker s manual aording to the shape. d. Grind the edges. e. Turn over the work-piee. f. Grind turned work-piee. g. Arrange the finished work-piee to the output palette for the next proess. It is very diffiult to develop fully automated grinding system for the all sub-tasks above; For example, it s hard to selet and load a work-piee from the palette that ontains mixed work-piees in various shapes and different sizes. In this work, therefore, we developed a grinding system for the seleted sub-tasks and left others as human worker s portion, so that we an implement the grinding system in given period and budget. Table 1 shows the property of the sub-tasks and our strategy to develop auto-grinding system. φ A= A0 k A sat τ s, (8) φ

4 Table. 1. Properties of sub-tasks and strategy for system development Sub- Property Strategy Task a b d,f e g Automati handling of palettes with few tons is not good approah. It s diffiult to selet and load one from a stok of mixed work-piees. It takes long time and expensive to develop auto shape reognizing system. It is needed to ontrol ontating fore and to trak the surfae of work-piees in various shapes. It must turn over workpiees of weight 20kg It is a simple task if system knows the shape and orientation of workpiees. Let workers move it using overhead rane. Ask workers to stok work-piees in a speified artridge. Load/unload devie moves them from the artridge to working plae. Let workers input the shape number. Develop a grinding robot with auto traking funtion. Develop a turn-over devie. Load/unload mahine moves the work-piees in working plae to the palettes. As a result, human worker does the first three sub-tasks in the developed system and the grinding robot system does the others; Human workers take work-piees from a palette, stak them in a speified plae, a artridge ell, and inform the grinding robot system the shape of the work-piees. Note that a artridge ell must inlude only one shape in predefined orientation. The grinding robot system, then, moves the work-piees to work plae, grinds them and staks them on an output palette. 4.2 Components in grinding robot system The developed grinding robot system onsists of three mehanial omponents and two sensing omponents. Mehanial omponents are a load/unload devie, a grinding robot and a turn-over devie. Two sensing omponents are a barode sanner and a laser distane sensor that are for informing shape number and measuring the dimension of work-piees, respetively. Load/unload devie is to move work-piees from artridge ell to work plae and from work plae to output palette. It an arry work-piees up to 20kg with its eletro-magneti hands. Sine artridge ells and work plae are loated in fixed plae. The load/unload devie simply travels between the pre-programmed positions. If it touhes the bottom of the artridge ell when it tries to pik up work-piees, it regarded that there is no more work-piees left. Grinding robot has six degree of freedom (DOF) and is equipped with a fore torque sensor to measure grinding fore. It is droved with position ontrol type servo ontrollers and trajetory and grinding proess is ontrolled by DSME s universal ontroller (Kim, 2005). Work-piee that was grinded by robot is turned over by a turn-over devie and the robot grinds the bakside. In order to inform the shapes of work-piees to the robot, operator must plae a appreiate barode at the speified plae and robot ontroller reognize the shape number through barode reader. A laser sensor was attahed to the tip of robot hand to measure the size, thikness and the loation of work-piees. Sine the shape and orientation of the piees are informed by operator, the size and loation an be estimated by measuring few ritial points aording to the shape. Fig. 5 shows an example of the ritial points for two types of work-piees and sanning path of laser sensor to measure the points. The dimension information is sent to the grinding robot ontroller so that it generates grinding information suh as approahing point, approah diretion, ending ondition and total grinding distane. Fig. 5 Critial points to measure the dimension of work-piee and sanning path of laser distane sensor 4.3 Real implementation and experimental results Shemati of grinding robot system and real system are shown in Fig. 6 and 7, respetively. Fore torque sensor used in this work is ATI 660/60 with IP65 speifiation and barode sanner is from Datalogi. A laser sensor of Kiene, LB301, is used to measure the dimension of work-piees. Fig. 6 Shemati of grinding robot system 4288

5 Fig. 7 Grinding robot system with loading/unloading system 24 shapes were tested in this system and suessfully worked. The grinding speed was 20mm/s and measuring time for size was 10s. Grinding time was 15s for the smallest piee and 90s for the largest one. It was slower than human workers 50mm/s for grinding speed and less than 1s for shape and dimension reognition. 5. SUMMARY AND FURTHER WORKS The produtivity is not as good as human workers. Yet, it ould remove workers from grinding work that ould be a ause of musle injury. Human operator, in the developed system, doesn t need to grind but just load work-piees and pushed operation buttons. Additionally, it ould work ontinuously without braking time and did not argue disease from ontinuous vibrating fore. There are many points to improve this system. Human workers wish to get full automated loading system that brings work-piees from palette to work plae and reognizes itself the shape of the piees. Inreasing the grinding speed and reduing the handling time are also asked for better produtivity. Optimal design of the system is another request. 3-DOF robot an replae the 6-DOF robot, beause the orientation of tool is fixed during grinding work. Sine the fore-torque sensor is too preise and expensive for this proess, simpler and more robust sensor will be appropriate suh appliations. Chang, P.H., D.S. Kim and K.C. Park (1995). Robust fore/position ontrol of robot manipulator using time delay ontrol. Control Engineering Pratie, Vol. 3, No.8, pp Choi, B.O. and M.K. Lee (1999). Position and veloity ontrol of a hybrid (parallel-serial) robot manipulator for propeller grinding. Journal of Control, Automation, and Systems Engineering, Vol. 5, No. 2, pp Choo, J.H, et. al. (2006). Auto path generation and ative ompliane fore ontrol using 3-axis grinding robot. Journal of Control, Automation, and Systems Engineering, Vol. 12, No. 11, pp Ferretti, G., G.Magnani and P. Roo (2000). Impedane ontrol for industrial robots. Pro. IEEE Int. Conf. Robotis and Automation, pp Hogan, N. (1985). Impedane ontrol: An approah to manipulation: Part I - Theory. ASME Journal of Dynami Systems, Measurements, and Control, Vol. 107, No.1, pp Hogan, N. (1985). Impedane ontrol: An approah to manipulation: Part II - Implementation. ASME Journal of Dynami Systems, Measurements, and Control, Vol. 107, No.1, pp Hogan, N. (1985). Impedane ontrol: An approah to manipulation: Part III - Appliations. ASME Journal of Dynami Systems, Measurements, and Control, Vol. 107, No.1, pp Jenkins, H.E, T.R. Kurfess and R.C. Dorf, (1996). Design of a robust ontroller for a grinding system, IEEE Transations on Control Systems Tehnology, Vol. 4, pp Kazerooni, H., B.J. Waibel and S. Kim (1990). On the stability of robot ompliant motion ontrol: theory and experiments. ASME Journal of Dynami Systems, Measurements, and Control, Vol. 112, No. 3, pp Kim, S.H., et. al. (2005). A robot ontroller development of a large-sale system for shipbuilding. Pro. Int. Conf. Control, Automation and Systems. Roy, Jaydeep and L.L. Whitomb (2002). Adaptive fore ontrol of position/veloity ontrolled robots: Theory and experiment. IEEE Transations on Robotis and Automation, Vol. 18, No. 2, pp Surdilovi, D. and J. Kirhoff (1996). A new position based fore/impedane ontrol for industrial robots. Pro. IEEE Int. Conf. Robotis and Automation, pp Surdilovi, D. (1996). Contat stability issues in position based impedane ontrol: Theory and experiments. Pro. IEEE Int. Conf. Robotis and Automation, pp Wang, Y.T. and Y.J. Jan (2000). A robot-assisted finishing system with an ative torque ontroller, Pro. IEEE Int. Conf. Robotis and Automation, Vol. 2, pp Waibel, B. and H. Kazerooni (1991). Theory and experiment on the stability of robot ompliant motion ontrol. IEEE Transation on Robotis and Automation, Vol. 7, pp REFERENCES 4289