Some criteria to help the experimental setup of assembly cells with cooperating robots

Robotics & Computer-lnteorated Man~acmrina, Vol. 12, NO. 2, pp. 125-133, 1996 Copyright © 1996 Elsevier Science Ltd Printed in Great Britain. All fights reaerved 0736-5845/96 $15.00 + 0.00

Pergamon

0736-5845(95)00014-3

•

Paper SOME CRITERIA PACIFICO

TO HELP THE EXPERIMENTAL SETUP OF ASSEMBLY CELLS WITH COOPERATING ROBOTS

M. PELAGAGGE,

GINO CARDARELLI

and MARIO

PALUMBO

Faculty of Engineering, University of L'Aquila, Piazza Rivera 1, 67100 L'Aquila, Italy

A pragmatic approach for aid in the designing of assembly cells with cooperating robots is presented in this paper. The conditions justifying the use of multiple cooperation have been previously defined. Effort was then focused on the appropriate characterization of the assembly tasks with the aim of helping find solutions for solving both collision and coordination problems: The capability of the laboratory used for experimental studies on cooperating robots is also illustrated. The presented criteria have been applied to the cell setup of a mechanical assembly process. Copyright © 1996 Elsevier Science Ltd.

1. I N T R O D U C T I O N The expansion of assembly automation technology towards applications with an increasing complexity level and reduced product lifecycles needs high flexibility solutions. There are many fields where this need is more strictly required. The first example concerns mechanical assembly processes consisting of tasks that require robots with different characteristics such as payload, velocity, repeatability and accuracy. In this case a significant operational capacity increase may evidently be reached using skilled robots which co-

The complexity of the problem often renders necessary heavy experimental analysis in order to guarantee a successful result. Bearing this in mind a methodology has been developed to help the experimental investigation. The major steps of such a methodology, regarding cell layout, assembly task characterization, precedence relationships, no-collision planning, have all been discussed in the paper. The experimental configuration used in the study has also been presented, characterized by a task level control, an efficient coordination and a large class of tasks to be performed. Finally, an application example to illustrate the ability of the method has been presented, concerning the assembly of an electromechanical product that features skilled operations, many assembly directions and some tasks that require multiple cooperation. The results demonstrate the capacity of the approach in designing and implementing effective assembly cells.

operate.3,6,7,1 o, 27

Furthermore, an assembly process presenting many assembly directions calls for generalized fixtures which may be conveniently realized by a cooperating robot.6,8,26,3 o

The last important example regards an assembly task containing operations that cannot be carried out in any way by only one robot. 21'22'26'34 In these three cases, resorting to assembly cells with cooperating robots clearly allows for both a flexibility increase and a higher reconfiguration capacity. Cooperating robot applications, however, involve a lot of conceptual and practical problems linked to coordination, 12-x4Aa'21-24'2a'31'32'34'35 sequencing, 2'5-7A°'27 collision La'g'rAS'17'29,33 and communication architecture. 9'1tA9'25'26'35 The aim of this work concerns the definition of design criteria for assembly cells that have to carry out a process presenting one or more of the aforementioned characteristics:

2. CRITERIA FOR MULTIROBOT ASSEMBLY

CELL DESIGN 2.1. Problem statement This work deals with assembly cells where: • N defined components have to be assembled; • each component to be assembled is always available. The assembly process presents one or more of the following constraints: • some assembly tasks require skilled robot; • some assembly tasks cannot be carried out by one robot alone; • different assembly directions call for versatile fixtures.

• skilled robots are required; • different assembly directions are involved; • one robot alone is not able to perform some assemblies.

In the described scenario, an assembly cell using two or more cooperating robots may conveniently be used. 125

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Robotics & Computer-Integrated Manufacturing • Volume 12, N u m b e r 2, 1996

which discriminate the critical area and the nocollision areas. This approach may easily be extended to three robots and other robot morphologies (i.e. Scara), resorting to the concept of major and minor link. 1° Regarding, instead, the component feeding systems, the pick points have to be obviously allocated inside the no-collision area. The pick point positions will be optimized during the assembly planning phase.

Fig. 1. Critical area definition.

An appropriate design of the assembly cellrequires the layout definition,the non-skilled tasks assignment and the task sequencing, guaranteeing in every way nocollision and coordination between the cooperating robots. With this aim some criteria have been developed which will be distinctly illustrated in this paper, regarding: * cell layout; . assembly task characterization; o precedence relationships; • no-collision planning. The use of the suggested criteriafor the assembly cell setup is,however, strictlyinterrelated. 2.2. Cell layout In the hypothesis that each component can be picked up by one robot alone, a first criterion for the layout definition may be the minimization of the shared area (called hereafter critical area), increasing the nocollision workspace of each robot. This means that the critical area has to match the particular product to be assembled. With reference to two articulated robots and considering the transportation layer only, 6 the critical area is immediately defined as in Fig. 1, where ~ and fl represent the angles

2.3. Assembly task characterization A generic assembly task may now be subdivided into two types of activities: outside the critical area and inside the critical area. Generally speaking, the activities outside the critical area can include component pick and critical area approach actions, those inside the critical area, instead, target approach, assembly and critical area exit actions. Each action normally consists of elementary robot actions such as move, open, etc. A classification example of the actions carried out during an assembly task is shown in Fig. 2. Obviously the actions inside the critical area only present collision risk. This type of task characterization allows for the defining of both the time of outside critical area (TO) and inside critical area (T/) activities. The evaluation of TO and TI may be carried out either by analytic calculation or by experimental analysis. In the first case, sophisticated algorithms for robot modelling must be available. In both cases a method study of the robot carrying out the assembly task is always necessary. 2.4. Assembly task connection levels Depending on the complexity of the assembly task, a low connection level and a high connection level may be defined.

Low connection level. This connection level involves

, ASSEMBLY TASK I

Outside

move

critical

move

area

close

Inside

activities

move

move

move

critical

move

area

open I

approach to critical are•

approach to pick point

ETO

STO

TO

Fig. 2. Assembly task characterization.

approach to target

activities

move

move

I

[assembly]

exit from critical area ETI

STI t
Experimental setup of assembly celb • P. M. PELAGAGGE et al.

127

Task Ak

aik constraint

noint

T a s k Ah Fig. 3. Constraint point definition.

tasks that may be carried out by one robot alone; two cases are possible: (1) skilled assembly task assigned to robot R~; (2) non-skilled assembly task assigned to robot Ri or

Rj

T a s k Ak q Outside critical / area ativities /

Inside critical area activities

TO

TI

constraint

TO

In both cases the robot coordination must just avoid collision between robots performing different tasks.2S,26, 33

High connection level. The assembly task has to be assigned to two robots R i and Rj; that is, both robots have to contemporaneously work inside the critical area. Two principal cases may be pointed o u t : 7'25.2s, 33 1. Serialized motion actions. The assembly actions taken by the different robots are independent: the robot Rj must wait for the robot Ri to complete before it can start (i.e. one robot has been used as a generalized fixture for another robot). 2. Tightly coupled actions. The assembly actions taken by the different robots to achieve sub-goal, depend on each other (i.e. two robots which have to handle the same object). In the first case, no-collision and synchronization between the cooperating robots have to be assured only during the inside critical area actions. A more strict motion coordination is instead required in the latter case; 35 that, however, occurs rarely in mechanical assembly processes. With the aim simplifying the next assembly planning phase, the equivalent duration of activities outside (TOeq)and inside (T/eq)the critical area may be defined (Fig. 2):

TOeq = min[ ETO( R,), ETO(Rj)]

-min[STO(R,), STO(Rj)] Tleq = max[ ETI( R~), E TI( R j)] -min[STO(Ri), STO(Rj)]'TOeq. This is a conservative way to discriminate between outside and inside critical area activities for high connection level assembly tasks. As a consequence of the previous definitions, three

T area

point

i ............. T I ..............

I

activitie~

area

Task

activities

A~

Fig. 4. Hypothesis on constraint point.

types of block can be used to represent any assembly task: SKILLED TASK robot assignment R i task times TOt, TI i NON-SKILLED TASK robot assignment R~ or Rj task times TOi, TIi or TO j, TIi COOPERATING TASK robot assignment R~ and Rj task times TOeq, Tleq. 2.5. Precedence graphs The blocks representing the tasks may be interrelated by precedence relationships linked only to assembly process requirements. An assembly process may be well represented, combining serial and parallel schemes. The serial scheme states a constraint point between the end of the action ask belonging to task Ak and the start of the action a~h belonging to task Ah (Fig. 3). The parallel tasks instead can be contemporaneously carried out from the viewpoint of the assembly process. A lot of precedence graph types were proposed to represent different assembly processes. 3° However, in mechanical assemblies, prevalently serial precedence relationships frequently occur. On the other hand, the need to avoid collision often determines that parallel actions cannot really be

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Robotics & Computer-IntegratedManufacturing• Volume12, Number2, 1996

T2

Fig. 5. No-collisioncondition. carried out at the same time. This condition introduces a constraint point for the parallel tasks and determines a constraint point shifting for the serial tasks. Adopting a conservative hypothesis, the constraint point has been in all cases allocated on the border between outside and inside critical area activities (Fig. 4). The identifying of the parallel activities that can actually be carried out at the same time, from the collision viewpoint represents, therefore, a relevant knowledge base for the assembly cell. Considering two assembly tasks with target points T1 and T2, a necessary condition to guarantee collision-free motion requires no intersection between the robot arms when the respective target points are reached (Fig. 5). Such a condition is normally also sufficient if the pick areas of the two robots are opposite with respect to the critical area. The pick points of the components to be assembled on target points /'1 and T2 can be chosen in order to optimize the paths and the times TO and 1"1 of the contemporary tasks. 2.6. No-collision assembly planning Considering assembly tasks as operations sharing the critical area, the no-collision planning problem can be reduced to the defining of the order followed by the tasks to seize the critical area. Two sub-problems may be formulated: • sequencing of parallel tasks; • robot assignment to non-skilled tasks. Many approaches to scheduling precedence constrained operations are presented in the literature. 5-7'1°'16'2°'27'a° In order to reduce makespan, the maximization of critical area utilization level has been pursued during the no-collision assembly planning phase. A very simple approach has been adopted here: step 1 define the precedence graph adopting a tentative allocation of component pick points on candidate positions (Fig. 6a); step 2 modify the precedence relationships in order to introduce the collision constraints on parallel tasks

(the step obviously increases the series content of the precedence graph, Fig. 6b); step 3 define the task order to seize the critical area adopting the hypothesis: assign each non-skilled task to the robot with lowest TI, without taking into account that the same robot may be simultaneously engaged with another task (Fig. 6c). IF time-interferences on the same robot engaged in two different tasks do not occur when also the outside critical area activities are considered THEN the planning represents an overall optimal solution IF time interferences occur THEN the planning represents a reference ideal solution (Fig. 6c) and step 4 must be carried out; step 4 examining in chronological order the start time of the tasks, eliminate the time-interferences using in sequence the criteria (Fig. 6d) (a) search for the allocation of component pick points on candidate positions able to match the time of outside critical area activities to the robot availability; (b) modify the robot assignment to non-skilled tasks; (c) delay the task start times. The robot assignment modification leads to a start time shift of the inside critical area activities for all the following tasks. During the application of such a criterion, the minimization of the start time shifts has to be pursued. A value equal to one has, however, been obtained for the critical area utilization level. If delays of task start time must be introduced in order to eliminate residual time-interferences, then the critical area utilization level evidently decreases. An interactive algorithm has been developed according to the proposed criteria.

3. LABORATORY DESCRIPTION In order to develop applications with cooperating robots and to verify different solution methodologies, an experimental environment has been used. 3.1. Robot characteristics The laboratory is equipped with four Eshed robots featuring different arms of both articulated and Scara morphologies. The controller peculiarities are instead the same for all the robots. In particular the following principal operational capabilities are available on each robot controller: • CPU Motorola 68020, real time, multitasking, stand alone, PID; • continuous path control; • 16 input and 16 output channels; • communication by standard serial port (RS232); • definable time or speed between points. These capabilities look very favourable in cooperating robot applications, since the multitasking allows

Experimental setup of assembly cells • P. M. P E L A G A G G E et al.

r~j TASK A. B C D g F G H

(a)

•rA~sK ~ o ~ B C D Jg F G H

1 2 2 2 2 2 1

~

i

B

t

~

t

Robot I TOI TII

to

8

/

/

o

5

4 8 8

4 4

7 6 6

6 6

Robot 2 TO2 TI2

/

/

8

12

6 6 6 5 5

/

9 4 4 5 5

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(c)

(b)

/

' 7 ,o7,

TO

w'n

129

! Z 2 2 1 2 1

TO i

~

m?I

,, i

¢

(d)

Fig. 6. Planning steps. Table 1. Robot specifications

Robot specifications

ER III

ER V

ER VII

ER 14

Payload (kg) 1 Max. speed (mm/sec) 330 Repeatability (mm) 0.5

1 600 0.5

2 1000 0.2

2 2800 0.05

commands arrangement in a timely manner helping towards an effective and efficient robot synchronization. The robot specifications are summarized in Table 1.

Fig. g. Centralized-decentralized architecture.

3.2. Robot coordination Two different coordinated motions are allowed by the hardware-software characteristics of the laboratory cooperating robots, that are point-wise and trajectory-wise. 35 The point-wise coordination may be pursued following two strategies: by coordination signals when the goal points of cooperating robots are reached; and by time control synchronizing the move duration of cooperating robots. Combining both strategies, pointwise coordination can be effectively and efficiently executed. 35 The trajectory-wise approach, instead appears strictly necessary only for robots handling the same object; such a situation obviously introduces kinematics constraints on the entire motion trajectories of the coordinating robots. In this case the Cartesian trajectories of cooperating robots, in terms of end-effector position and orientation, have to be computed according to the desired object trajectory and the constraint conditions imposed by the object. The robot trajectories are therefore transferred to the corresponding controller and implemented using appropriate continuous paths under time control.

for running up to 20 programs simultaneously; the stand alone makes necessary the PC for the programming stage only; the continuous path control allows for the use of linear and circular moves but also of any other move along paths calculated by mathematical formulas; the input-output on/off channels allow for low level robot coordination and also for device control (output channels) and event monitoring (input channels); the R$232 ports allow for high level robot coordination; definable move time or speed allows for

3.3. Robot communication For both coordination approaches, if the tasks to be carried out are univocally assigned to the robots during the planning phase then the communication between the robot controllers involves synchronization signals only. In this case a distributed architecture (Fig. 7) clearly satisfies the communication requirement. The real time synchronization has been obtained using the I/O channels and the input interrupts

I~-232

iCls°nut:°/telrnrulT, Cs°ntr°:le:~

I~

"

~

Cm°ntr°lleru3T

~

'1

Fig. 7. Distributed communication architecture.

~RS

-232

Controller 1 L~PUY

OWI~UY

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Robotics & Computer-Integrated Manufacturing • Volume 12, Number 2, 1996

sufficient for a large class of mechanical assembly processes. 19 20

18

Fig. 9. Assembly process example.

available on the laboratory robot controllers. The PC works exclusively as a terminal for starting the application and for showing the system condition. In a non-deterministic assembly environment where some tasks may be indiscriminately carried out by different robots (i.e. random arrival of components to be assembled), the use of a centralized--decentralized architecture offers some advantages. 19'25'26 On the one hand, in fact, the cell management requires a master device as supervisor, on the other hand the type of messages to be handled is no longer binary, thus calling for high level interfaces. In order to make optimum use of the capabilities of the laboratory robot controllers, an architecture foreseeing a controller as master for supervision and communication management has been adopted in this case (Fig. 8). A point-wise coordination with a distributed communication architecture appears, however, to be

Fig. 10. Experimental installation.

4. EXAMPLE OF ASSEMBLY CELL SETUP The proposed criteria have been applied to the setup of a cell which has to perform the assembly process schematized in Fig. 9. The process presents four different assembly directions and calls for an accurate positioning of some components, namely, components 2, 5, 19 and 20. Furthermore three sub-assemblies, which are component 11 on 12, component 17 on 18 and components 19 and 20 on 18, need multiple cooperation. As a consequence, the use of three robots has been decided (Fig. 10): • one 4-axis Scara robot (R1); * two 5-axis articulated robots (R2, R3). The robot R a has been used as a general fixture for the orientation of component 1, allowing for the vertical insertion of components by the Scara robot. The robot R 2 has been used as a cooperating robot during the aforementioned sub-assemblies and also as an alternative robot for non-skilled tasks. In this way the elimination of dedicated fixtures and orientation devices has been possible. The precedence graph for the assembly process is shown in Fig. 11. Prevalently serial precedence relationships characterize the mechanical assembly process. In the blocks, other than the robots and the times, the components to be assembled are indicated too. In order to define the task times both a method study and an experimental measure campaign have been

Experimental setup of assembly cells • P. M. P E L A G A G G E et al.

I

!

E

I R3 oed RI R3.--* T01=13.49 T11=6,84 RJ ~ TO2=4.?I TIE=IO.30

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I

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r

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'

R3 o~1 (RI o r R2) RI ~ T04=3.76 TI4=9.E9 RE "-," T04=3.90 TI4=I44S5

1"I3='10.76

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131

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[

I

R

R

~/AITING POINT

I R3 ond RI

R3-* RI ~

T01=O T05=3.81

TII=4.13 T|5=9.39

1+11+12

Fig. 12. Cooperating assembly of 11 on 12 on 1. I

1 6 R3 of~l (RI o r RE) RI .-~ TD6=3.55 T16=10.54 R;:-.~ TO6=3.3E T16=14.(~.

I 1

R3 ,',rid (RI R3 -b T O ] = O RI - " T0"/=3.67 RE "-" TOT=3.TE

I

1

VAITING POINT 7

o r R2)

T11=9.04

T17=9.37 T17=9.81

• R 2 orientates the component 12 (TO=2.92 sec, TI= 5.54 see); • R 1 assembles the component 11 (TO=3.63 sec, TI= 6.92 see); • R 2 assembles the component 12 (TI= 14.47 see).

8

Block B works in the same way:

R3 ond (RI o r RE) T08=4.01

I

2

R 2 orientates the component 18 (TO=3.13 sec, TI= 8.44 sec); • RI assembles the component 17 (TO=3.91 sec, TI=6.13 see); • R 2 assembles the component 18 (TI= 13.83 sec). •

T18=8.97 9

R3 ond (RI or" R21 Rt --~ T09=3.82 TIg=7.EI R2..-t,, T09=4.01 T19=5.67

[ 1

10

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tit0:706

I 1

A

II

12

R3 ond RI ond R2 TOeq=E.9~, TIeq'.E6.93

I

I 1and (R) o~13 R~)

R3 K5 --p T013=3,55 Tn3=9.75 R2--~ TOI3=4.E2 T113=9.02

]

I I 14 R3 ond (RI or- R2) RI ..e TOI4=4.71 TI14,,10.10 R2-J. TOI4.,,4.1E T114,,,9.18

I

I

t

VAITING POINT

15 R3 (and (RI or" R2) R3--* TOI=O TII=5.12 RI .-t. T015=4.87 "I]15=7.2E R2--* T015=3.53 T115=5,70

I l

16 R3 a ~ (RI or" RE) RI "-~ TO16=3.85 TI16=~97

R 2 ~ TO1&=5.10 TIIG=63.E

I 1

t3

17

18

R3 and RI ana RE TOecl=3J.3 Tleq-8?.40

During the assembly of components 19 and 20 (blocks C and D), the robot R 2 acts as general fixture for the component 18. Three waiting points 6 may be defined, corresponding to the orientation changes of component 1. For every task following each waiting point, the robot R 3 acts naturally as general fixture for the component 1 only. The maximization of critical area utilization level obviously has to be pursued only for tasks comprised between the waiting points. The planning problem, in this case, requires the defining of the sequencing of parallel tasks and of the robot assignment to non-skilled tasks. The planning shown in Fig. 13 has been obtained following the proposed criteria. The effectiveness of the assembly cell setup may be in this case measured by the critical area utilization level: ~ TI = 0.98. MAKESPAN

I I

C

18

19

R3 ond RI and RE

RI .-b 7019=3,76

TI19=9.44

I

D

l

1 18 20 R3 Qnd RI and RE RI - " TOEO=-4.69 TI~0=9.09

Fig. 11. Precedence graph.

carried out for each precedence block. The block A representing a multiple cooperation performs the following activities (Fig. 12):

5 . CONCLUSIONS A pragmatic approach for the setup of assembly cells with cooperating robots has been presented in this paper. The characterization of the task by outside and inside critical area activities allows for the solving of both collision and coordination problems. The proposed planning rule appears able to find an optimal solution which guarantees the minimum makespan maintaining high value for the critical area utilization level. The interactive nature of the planning algorithm

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Robotics & Computer-Integrated Manufacturing • Volume 12, Number 2, 1996 Component TI ( m o v e 3 2 ! 3 ! 2 3 2 I 2 l 2 ! 2 1 2 3 2 ! 2 1 2 I I

in critical

area)

1 a 4 1 5 6 1 7 8 9 10 [2 1! 12 13 14 1 15 t6 18 17 18 19 2O

,

I"] ( w a i t i n c r i t i c a l

,

TO

area)

4

Fig. 13. Assembly planning. represents a useful help towards the cell layout definition too, optimizing in particular, the allocation for the pick point positions of the components to be assembled. M a n y laboratory tests have been carried out in order to verify experimentally the validity of the suggested criteria, confirming the approach capacities in rapid and effective assembly cell setup. REFERENCES 1. Basta, R. A., Mehrotra, R., Varanassi, M. R.: Detecting and avoiding collisions between two robot arms in a common workspace. Robot Control Theory Applic. 185-192, 1988. 2. Ben-Arieh, D.: Concurrent modeling and simulation of multi-robot systems. Robot. Comput.-Integrat. Mfg 8: 67-73, 1991. 3. Cao, B., Dodds, G. I., Irwin, G. W." Fast collision detection and avoidance in a multiple manipulator environment. In Proc. of lASTED Int. Conf. on Robotics and Manufacturing. 1993, pp. 127-130. 4. Cela, A. S., Hamam, Y. H.: Optimal motion planning of a multiple-robot system based on decomposition coordination. IEEE Trans. Robot. Autom. 8: 585-596, 1992. 5. Chen, Q., Luh, J. Y. S.: Task level optimum scheduling by truncated Petri nets applied to operation of multirobot workcell. In IEEE Int. Conf. Robotics and Automation, Vol. 3. 1993, pp. 326-331. 6. Cheng, X.: On-line path planning for assembly operations by a two-arm robot. In Proc. IASTED Int. Conf. on Robotics and Manufacturing. 1993, pp. 108-111. 7. Coupez, D., Delchambre, A., Gaspart, P.: The scheduling of a multiple robots assembly cell. In Proc. 5th CIM Europe Conf. 1989, pp. 185-195. 8. Duffy, N. D., Herd, J. T., Philip, G. P.: A structured approach to the control of parallel acting co-operating robots. In Proc. Int. Syrup. Industrial Robots. 1988, pp. 323-332. 9. Freund, E., Robmann, J.: Autonomous operation of multi-robot-systems in factory of the future scenarios. In 6th Int. Conf. CAD/CAM, Robotics and Factories of the Future, Vol. 1. 1991, pp. 269-274. 10. Fu, L. C., Hsu, Y. J.: Fully automated two-robot flexible assembly cell. In IEEE Int. Conf. Robotics and Automation, Vol. 3. 1993, pp. 332-338. 11. Gauthier, D. et al.: Interprocess communication for distributed robotics. IEEE J. Robot. Autom. RA-3: 493-504, 1987.

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