The validity of equation (1) is based on two ... This system of equations can be solved for the .... [3] Watson, P.C. and Drake, S.H.: "Pedestal and Wrist Force.
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Sensing in Robotic Control
Apply Force/Torque Sensors to Robotic Applications Jay Lee Robotic Vision Systems, Inc., Hauppauge, New York 11788, U.S.A. Over the last ten years the state-of-the-art in robotic force/ torque sensors has been developed to a high degree in research laboratories. Unfortunately, such systems have not found much use outside of the laboratory because of high cost and sophisticated system software. This paper will present how the force/torque sensor has been implemented in robotic applications such as grinding/deburring, drilling and assembly for industry and military. Overload sensing and robot programming by use of force/torque sensors are also presented.
Keywords: Sensors, Programming
1. Introduction Over the last ten years the state-of-the-art in robotic force/torque sensors has been developed to a high degree in research laboratories. Unfortunately, such systems have not found much use outside of the laboratory because of high cost and sophisticated system software. This paper will present how the force torque sensor has been implemented in robotic applications such as grinding/ deburfing, drilling and assembly for industry and military. Overload sensing and robot programming by use of force/torque sensors are also presented.
2. Rol~tic Force/Torque Sensors There are several different types of robotic force/torque sensors which have been used in the robotic field: Robot joint force/torque sensors (Fig. 1 ), robot wrist force/torque sensors (Fig. 2) and force pedestal. The following criteria are used to choose the right force/torque sensor: a. high stiffness b. compact design c. good linearity d. low hysteresis and friction.
~TORQUE SENSOR North-Holland Robotics 3 (1987) 189-194
Fig. 1. Robot joint force/torque sensor.
0167-8493/87/$3.50 © 1987, Elsevier Science Publishers B.V. (North-HoUand)
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The basic sensor calibration procedure consists of applying 6 known linearly independent sensor loadings F k, k = 1 . . . . . 6, and recording the resulting strain gauge readings S k. The components of F k and S k are denoted by F k r j = l . . . . . 6, and Ski, i = 1 , . . . , n, respectively. The technique used to solve for C involves first solving for C*, the pseudo-inverse of C, an n × 6 matrix which satisfies
UE SENSOR
J
I
C *C = I , ,
Fig. 2. Robot wrist force/torque sensor.
(2)
where 1, is the n × n identify matrix [2,3]. Multiplying both sides of equation (1) by P gives
Fig. 3 is a representation of the f o r c e / t o r q u e sensor coordinate system. Load applied to the sensor can be resolved into six cartesian f o r c e / torque components denoted by the vector F = ( Fx, Fy, Fz, Mx, My, Mz) where the first three components represent forces acting parallel to the x, y, z axes and the last three components represent torques about the x, y, z axes respectively. Let S = (Sa, Sz . . . . . S,) represent the strain gauge readings output by the sensor under load F, where n is the number of strain gauges in the particular sensor being used. Then F and S are related by r = c-s,
(1)
where C = (Cu) is calibration matrix. Equation (1) provides the means for transforming raw strain gauge readings into cartesian f o r c e / t o r q u e components [11]. The validity of equation (1) is based on two assumptions regarding the sensor: 1. Linearity: the response of the strain gauges varies linearly with the load applied to the sensor. 2. Superposition: the effects on each strain gauge reading due to the individual components of F are additive.
C * F = C * C S = I , S = S.
(3)
The entries of C* are solved for one row at a time using the calibration data F k and S k. For each row i of C*, we can write six equations in the six unknowns Pi,, Pi2 Pi, as follows: . . . . .
Ci*l Fkl " --~ Citlk
2 ~- ...
-4- Ci6~k6 :
Ski , k = 1 .....
This system of equations can be solved for the Ci~ by any standard method of solving simultaneous linear equations. Repeating this procedure for i = 1, 2 . . . . . n yields a complete solution for C*. Finally, the calibration matrix C is obtained from the following matrix equation:
C= ( c * T c * ) - I c *T
APPLY FORCE
GET C* FROM EQUATI ON C*F=S
Fy C=(c*Tc *)-IC::T
MX F=CS FZ
Fig. 3. Coordinate system of a force/torque sensor.
6.
(4)
Fig. 4. Calibration procedure for force/torque sensor.
(5)
J. Lee / Apply Force~ Torque Sensors to Robotic Applications
Fig. 4 shows the flow chart of calibration procedures.
3. Apply Force/Torque to Robotic Grinding/ Deburring Applications Almost all manufacturing processes applied in machine building result in a formation of burrs with different shape and size. When it is a matter of small burrs, automatic deburring processes such as chemical milling and electro-chemical milling methods may be used. When it is a question of large burrs, there is no automatic deburring process. In the past few years, industrial robots have been used for robotic deburring applications. However, the majority of the currently known applications of industrial robots for deburring are working without sensor. Positioning tolerance and tool wear can be compensated by an elastic suspension of the tool. A number of distinct approaches to the problem for controlling the contact force between a robot end-effector and a workpiece have also been used. Hybrid position/ force control [4-6] partitions the force control problem using a set of position and force constraints that depend on the mechanical and geometric characteristics of the task to be performed. Impedance control is a general approach to robot motion and force control that attempts to make a manipulator behave as a mass-spring-dashport system. Position and force control are considered two forms of impedance control. Position control implies very high impedances while force implies the opposite. Joint torque control alters the torque of individual servo-motors to achieve force control at the endpoint of the arm. The torque changes can be calculated by using either "computer torque" methods or direct feedback methods. Paul [7,8] implemented torque control on two axes of a Stanford manipulator by adding a torque feedback loop to the axis position control loop. However, the system was not used to control the force applied to the environment, but rather to reduce the frictional torques of the motor-tachometer assembly. The most straightforward approach is direct force sensing. There are two direct sensoring methods: 1. Severing of reaction forces on a work table (or pedestal) with built-in force sensors or wrist
191
force sensing. For pedestal force sensing, the work forces are measured on the work table. Transformation of the transducer output into assembly forces is performed by a computer program. 2. As for the wrist force sensing, reaction forces at the wrist of a manipulator produced by the contact between a tool and a part are measured. A six axes force/torque sensor can be used for this purpose. The three force and torque components can be determined by the signals of the strain gauges with a digital computer or with an analog computer circuit. Fig. 5 shows the adaptive control for contour tracking by a robot. This control approach enables the robot to follow a path that is not clearly defined and which deviates from the programming path. With adaptive control, tools such as polishing brushes can be used, regardless of the changing part contour. Adaptive control also compensates for wear of the brush. Although there have been various kinds of robotic applications in deburring, polishing and routing, the grinding automation for large scale and complex geometrical surfaces has not been realized because of the following reasons: 1. inaccuracies of the robot
(SOURCE: jR3)
work surface J
1 j
~
3 '
/
4 • Jr# f • programmed path
Fig. 5. Adaptive control of contour following. 1,4: no compensation is made 2,3: tool is compensated according to reaction force.
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MICRO-~ ROCESSO
POIIItON |
CONTROLLER
GRINDING ROBOT
Fig. 6. Force/torque controlledrobotic disc grindingprocess. 2. complex combination of grinding patterns 3. difficulties in metal removal control. A robotic disc grinding ev~iluation task has been conducted by the author in 1984 [10]. The disc grinding parameters include grinding angle, grinding force, disc grit size and feed rate. In order to predict the grinding path profile, the grinding database is necessary. The grinding path profile and tool can be described as follows: W = K F ~1v b l o c l m dl D = KFa2VblOC2Ma2 T = KFa3Vb3OC3Md3.
Here, F: Grinding force (lb) V: Robot velocity (ipm) O: Grinding angle (Degree) M: Disc grit size (16 - 120) W: Width of the grinding path D: Depth of the grinding path T: Disc tool life (min). Under constant grinding angle and disc grit size, in order to maintain constant path profile, the robot velocity can be modified through force/ torque sensor feedback. The tool life also can be predicted through tool life prediction equation. The control diagram is shown in Fig. 6.
4. Applying Force/Torque Sensor to Robotic Assembly Applications In the past few years, the interest of providing in some cases a robot arm with an active adaptable compliant wrist (AACW) [11,12] has been largely emphasized. The main component of such a wrist is a five degree of freedom force sensor. Every axis is driven by a DC motor via a soft servo loop, with tachs and encoder feedback. The servo
gain as well as the torque saturation level are software adjustable. For every degree of freedom, the spring zero position, the spring stiffness and saturation level can be adjusted at any instant during the assembly operation. The possibility to adjust the different spring stiffness allows to obtain a compliant structure with variable compliance matrix. This eliminates the objections against special purpose compliance tools. By adjusting the zero position of the spring along the different degrees of freedom, the displacement or forces can be applied. This active adaptive compliance wrist can serve as a force sensing element. The Instrumented Remote Center Compliance (IRCC) [13] is another general purpose robot wrist sensor capable of contact detection, position and angle error measurement, and force/torque measurement. Instrumented compliance devices measure up the six components of relative displacement, three of linear position and three of angular orientation. IRCC is an RCC type of compliant structure with three elastomer shear pads and three dual axis photo-position sensors. Igcc can be used to perform assembly tasks. Subsequent deflection readings from the IRCC indicate that a problem has developed. For delicate assembly operations which require the robot assembly system to provide for force/ torque feedback from the gripper to the arm control system, the Institute of Micro-engineering of EPF-L [14] has developed a force sensor which offers quite new features. The transducer is composed of a deformable elastic structure and of a set of inductive displacement transducers which are used in a nonconventional way. The output of these transducers is digitized and processed by a microcomputer so that the components of a load force ( a n d / o r torque) applied to the transducer
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5. Applying Force/Torque Sensors for Robotics Drilling Applications
~MN IC I OMPUTER FORCT E O /RQUE"
Automating the drilling process by robots calls for on-line monitoring of drill conditions. One of the major problems is tool wear. Tool breakage or premature failure is another problem. Since the drill rotates at high speed and is embedded in the work piece while cutting, it is impossible to on-line monitor the drill condition by visual means. A force/torque sensor can be used to monitor the thrust force of the drilling process since thrust force is a good indicator of drill condition. Fig. 8 shows the thrust force curves under normal and wear conditions [15].
]
i
I
II
"
.
I
Fig. 7. Minicomputer controlled positioning system for robotic assembly.
may be expressed in any coordinate system. The modular conception allows the system to be fitted with different ranges of forces. A six axes degree-of-freedom force/torque sensor strain gauges type can also be used in conjunction with microcomputer controlled positioning systems for force feedback assembly systems. Fig. 7 shows the minicomputer controlled positioning system with force/torque sensor for robotic assembly.
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6. Overload Sensing Overload sensing allows the user to program appropriate limits for successful tasks and monitor actual values on a continuous basis. Overlimit conditions caused by collision, improper part weight or multiple part acquisition, nonrelease from fixturing, or part jamming can be determined. Overload sensing can protect tooling, product and machinery.
%
f
TOOL WEAR
240
240
200
200
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160
120
120
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~
80
80
40
40 ........ 0
_........ 5
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.
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20
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. . . . .
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Fig. 8. Thrust force sensing for drilling process.
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7. Robot Programming R o b o t p r o g r a m m i n g is a proven, efficient use o f these sensors. T h e i n s t a l l a t i o n of a specially e q u i p p e d f o r c e / t o r q u e sensor to a r o b o t a r m allows the user to guide a r o b o t t h r o u g h a desired task or process. T h e r o b o t changes p o s i t i o n b a s e d on the f o r c e / m o m e n t applied, the result being a fast, precise m e a n s of p r o g r a m m i n g c o m p l e x m o tions. W h i l e this t e c h n i q u e has been successfully used in p r o d u c t i o n systems for m o r e t h a n a year, it is in its infancy in terms of its p o t e n t i a l i m p a c t on robotics.
8. Discussion This p a p e r discussed the characteristics of the r o b o t i c f o r c e / t o r q u e sensing system. S o m e r o b o t i c a p p l i c a t i o n s in g r i n d i n g / d e b u r r i n g , a s s e m b l y a n d drilling have b e e n presented. T h r o u g h the direct sensing of c o n t a c t forces a n d torques the r o b o t can m o d i f y its l o c a t i o n in r e s p o n s e to r e a c t i o n forces, thus allowing m o r e intelligent tasks to b e performed.
References [1] Lord Corp.: Technical Manual for FT Series "Force/ Torque Sensors", April 1983, Revision 2.2. [2] Shimano, B.E.: The Kinematic Design and Force Control of Computer Controlled Manipulations, Stanford Artificial Intelligence Lab Memo 313, March 1978. [3] Watson, P.C. and Drake, S.H.: "Pedestal and Wrist Force Sensors for Automatic Assembly", Proceedings of Fifth International Symposium on Industrial Robots, September 1975.
[4] Mason, M.T.: "Compliance and Force Control for Computer Controlled Manipulators", 1EEE Transactions on Systems, June 1981, Vol. SMC-II, No. 6, pp. 418-432. [5] Raibert, M.H. and Craig, J.J.: "Hybrid Position/Force Control of Manipulators", ASME Journal of Dynamic Systems, Measurement and Control, June 1981, Vol. 102, pp. 126-133. [6] Craig, J.J. and Raibert, M.H.: "A Systematic Method of Hybrid Position/Force Control of a Manipulator", Proceedings of 1EEE Computer Software and Applications Conference, November 1979, pp. 446-451. [7] Paul, R.P.C.: Modelling Trajectory, Calculation and Servicing of a Computer Controlled Arm, Artificial Intelligence
Lab, Stanford University Memo 177, September 1977. [8] Wu, C.H. and Paul, R.P.C.: "Manipulator Compliance Based on Joint Torque Control", Proceedings 20th IEEE Conference on Decision and Control, December 1981, Vol. 1, pp. 265-270. [9] Luh, J.Y.S., Fischer, W.D. and Paul, R.P.C.: "Joint Torque Control by a Direct Feedback for Individual Robot", IEEE Transactions on Automatic Control, February 1983, Vol. AG-28, No. 2, pp. 153-161. [10] Lee, J.: Developing an End-of-Arm Tooling for Robotic Grinding~Machining Applications, SME Technical Paper, MS 85-370, Robotic End Effectors: Design and Applications Seminar, March 1985. [11] Gerelle, E.: "Force Feedback Control", Proceedings of Eight International Symposium on Industrial Robots, 1978, pp. 194-205. [12] Van Brussel, H. et al.: "Further Developments of the Active Adpative Compliant Wrist (AACW) for Robot Assembly", Proceedings of the Eleventh International Symposium on Industrial Robots 1981, pp. 377-384. [13] Seltzer, D.S.: A Robot Tactile Sensor for Six Degrees of Freedom Displacement Measurement, Charles Stark Draper Laboratory, Inc. [14] Gerard, Piller: A Compact Six-Degrees-of-Freedom Force Sensor for Assembly, Institute de Microtechnique, Ecole Polytechnique Fedfrale de Lausanne. [15] Lee, J.: Optimization of Robotic Drilling Process, University of Wisconsin-Madison Research Report, MS 1225.
