Grasping Algorithm for Varied Objects

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Grasping Algorithm for Varied Objects

Ho-Yul Lee Byung-Ju Yi Youngjin Choi*

Department of Electronic, Electrical Control, and Instrumentation

Hanyang University, Seoul, Rep. of Korea

{hoyul,bj,cyj}@hanyang.ac.kr

Abstract - To connect the robot with human life, we need

an effective grasping algorithm. The robot should be able to grasp varied object in varied environment. The elements necessary for grasping algorithm are as follows: First, when grasping the object with diverse sizes and shapes, the fingers have to contact with them as widely as possible. Second, the robot should be able to control the force imposed on the object by finger knuckles. Third, if the size and position of object are not known accurately, the robot should be able to grasp it effectively.

In this paper, we propose a grasping algorithm that can satisfy these conditions, showing the efficiency of this algorithm through the simulation.

Keywords - Grasping, Finger, Hand.

1. Introduction

Various skillful tasks which humans perform involve dexterous motions of the hand. Various research projects on hands been conducted in an attempt to recreate the dexterity of the human hand [2-7].

Robots have to grasp object with diverse sizes and shapes. Through visual sensors, robots recognize the position of object to approach and grasp object. When recognizing the position of the object through the visual sensor, it is very hard to recognize its shape, size and position correctly as shown Fig.1. Therefore, the correct position and size of a object are not known, the grasping algorithm should enable the robot to grasp the object appropriately according to little information.

When grasp diverse object, the robot should impose the appropriate force on them. The robot finger must be controlled to impose the same force on the object by each of its contacting joint. Moreover, this algorithm should be matched the algorithm and the real hardware by force sensing.

Figure 2 shows the case of grasping without force sensor. As shown in the figure, the robot finger imposes too much force on the object, breaking the object or fingers. On the other hand, Fig.3 shows the case where a finger of the robot did not contact the object. Therefore, we need a force control algorithm.

Fig. 1. Motivation of grasping Algorithm .

Fig. 2. Without sensing the status of contact .

Fig. 3. Without sensing the status of contact.

2. Kinematics

The hand of robot consists of several fingers, and each finger can express 3 degrees of freedom. The retracting action of fingers for grasping can be acquired through the control of orientation for the end-link of each finger. So, each finger is two redundancies. We propose method to grant diverse algorithms through these redundancies [9].

*Corresponding author

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Fig.4. Left Finger.

Fig.3 is the grasping behavior of left finger. The kinematics of one finger can be expressed as follow

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In this paper, we simulate the grasping algorithm of robot hand with 2 fingers as in Fig. 5.

Fig.5. Left and Right Finger.

3. Matching the algorithm and the real hardware

by force sensing

Author As seen in Fig.2 and Fig.3, when the grasping force is ignored, the robot finger imposes too much force on the object, breaking the object or fingers. Therefore, it is necessary to control the force with sensing.

Where, fij is a contact force that represents the force

measured by the sensor attached to the real hardware. With the sensor, the force imposed on each joint is controlled to approximately appropriate value, preventing the excessive grasping that may cause the break of object or finger, or the incomplete grasping where the finger does not contact to the object.

Fig. 6(a). Grasping Algorithm with Force Sensor.

Fig. 6(b). Grasping Algorithm with Force Sensor.

As a way to match the sensed contact force to the kinematics, we suggest the weighting matrix method [1].

Fig. 7. Control in consideration of Weighting. Fig.7 is the control method in consideration of weighting. When the first link contacts the object, the value of W11 is given. Giving large weighting to the

motion of the first joint, movement of T11 is decreased and

movement of T12 , T13is increased.

The physical meaning of this algorithm is that the movement of corresponding joint is reduced, while the other joints are bent relatively more [8].

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, K : Arbitrarily constant f : Sensing force

4. Control position Y of end-point

Sometimes, the object is grasped by fingertip. In this case, if contact position Y of the right and left fingertip are different, the object cannot be grasped stably. So, it is necessary to control the position Y of fingertip when grasping.

Fig. 8. The object is on the center

Fig. 9. The object is on the right.

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Fig. 8 shows the grasping when the object is on the center. We can see that the Y contact points of two fingers are same. In this case, this grasping can be said stable. But, as in Fig. 9, if the position of matter is biased to the right, the Y contact points of two fingers become different, tilting the object. To remove this phenomenon, we need the algorithm to coincide Y contact points of two fingers.

By controlling the orientation of end-link, we can give the retracting motion to the finger. The distance between Y points of two finger ends is controlled to be minimized.

5. Simulation

In order to simulate, we need to measure contact force of each link. In this simulation we define that contact force is minimum distance between the surface of each link and position of the object as shown fig.10. If the length of di

is larger than 0, the contact force of i-th link is closed 0 ( 0.000001). Otherwise the contact force of i-th link is

i

d

.

Fig. 11 shows the experimental result of algorithm where the sensed forces are matched to the weight matrix. Here,

U

_L

[ 5 / sec]

D

, and

U

R

[5 / sec]

D

. With this

input, the fingers are retracted inward. In this Fig.11, we can see that, in grasping diverse object with different position, shape and size.

Fig. 10. Contact force

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-10 -8 -6 -4 -2 0 2 4 6 8 10 -4 -2 0 2 4 6 8 10 -10 -8 -6 -4 -2 0 2 4 6 8 10 -4 -2 0 2 4 6 8 10 -10 -8 -6 -4 -2 0 2 4 6 8 10 -4 -2 0 2 4 6 8 10 -10 -8 -6 -4 -2 0 2 4 6 8 10 0 2 4 6 8 10 12 -10 -8 -6 -4 -2 0 2 4 6 8 10 0 2 4 6 8 10 12

Fig.11. Result of Algorithm Simulation in consideration of Weighting.

Fig. 12. Result of Y-position Control.

Fig.12 is the result of simulation with the algorithm which matches the Y positions of two finger ends. As shown in the fig.12, even when the object is not positioned on the center of hand, it can match the Y contact points, enabling the stable grasping.

Fig. 13. Result of Non Y-position Control.

6. Conclusions

This paper has suggested an algorithm for the stable grasping even when the position, size and shape of the object to be grasped by the robot are not known correctly. We suggested algorithm, which is matching the algorithm and the real hardware by force sensing.

Through the simulation, it was shown that the algorithm suggested in this paper was useful in grasping diverse object.

Acknowledgement

This work was supported in part by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (R01-2008-000-20631), and in part by the Ministry of Knowledge Economy (MKE) and Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project for Strategic Technology, and in part by Ministry of Knowledge Economy (MKE) under the Human Resources Development Program for Convergence Robot Specialists, Republic of Korea.

References

[1] Y. Nakamura, Advanced Robotics, Publisher, Addison-Wesley Publishing Company, 1991.

[2] J.K.Salisbury and B. Roth, Kinematic and Force Analysis Articulated Mechanical Hands, Trans. ASME, Journal Mechanisms, Transmissions, and Automation in Design, vol 105, pp. 35-41, 1983.

[3] V. Nguyen, Constructing Stable Grasps in 3D, Proc. Of IEE Int. Conf. on Robotics and Automation, pp. 234-239, 1987.

[4] B.-J. Yi, S. -R. Oh, and I. H. Suh, 1999, "A Five-bar Finger Mechanism Involving Redundant Actuator : Analysis and Its Application," IEEE Trans. on Robotics and Automation, Vol. 15, No. 6, pp. 1001-1010.

[5] B. H. Kim, S. R. Oh, B.-J. Yi, and I. H. Suh, 2002, "Compliance Planning for Dextrous Assembly Tasks Using Multi-fingered Hands´,QWHOOLJHQW$XWRPDWLRQ and Soft Computing, Vol. 8, No. 1, pp. 51-64.

[6] B.--<LHWDO³Design of a Parallel-type Gripper Mechanism´ ,QWHUQDWLRQDO -RXUQDO RI 5RERWLFV Research, Vol. 21, No. 7, pp. 661-680.

[7] B. H. Kim, B.-J. Yi, S.-R. Oh, and I.H. Suh, 2004, ³Non-dimensionalized Performance Indices Based Optimal Grasping for Multi-fingered Hands´0HFKDWURQLFV9RO1RSS-280.

[8] Chan, T.F. and Dubey, R.V., ³$:HLJKWHG/HDVW-Norm Solution Based Scheme for Avoiding Joint Limits for Redundant Joint Manipulators,´ IEEE Transactions on Robotics and Automation, Vol. 11, No. 2, April 1995. [9] Luck, C.L. and Lee, S. ³6HOI-motion Topology for

Redundant Manipulators with Joint LLPLWV´ 3URF IEEE International Conference on Robotics and Automation, pp. 626-631, Atlanta, 1999.

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Grasping Algorithm for Varied Objects