- Open Access
- Authors : Prashanna Rangan R, Nithish K, Vishnu Chandran R, Arul Kumar M
- Paper ID : IJERTCONV10IS08053
- Volume & Issue : ETEDM – 2022 (Volume 10 – Issue 08)
- Published (First Online): 30-07-2022
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Design and Analysis of a 3-Finger Adaptive Gripper
Prashanna Rangan R* Department of Mechanical Engineering Sri Venkateswara College of Engineering
Sriperambudur, India.
Vishnu Chandran R Department of Mechanical Engineering Sri Venkateswara College of Engineering
Sriperambudur, India.
Nithish K
Department of Mechanical Engineering Sri Venkateswara College of Engineering Sriperambudur, India.
Arul Kumar M
Department of Mechanical Engineering Sri Venkateswara College of Engineering Sriperambudur, India.
AbstractIn today's modern industrial need a gripper becomes a vital element for handling components. A gripper is chosen based on the material to be handled and its properties. For any gripper to function effectively, its end application along with the work environment parameters has to be kept in mind while designing the gripper. Based on the trials conducted, the design concept is provided as part of an inventive gripper research project. The motive of this paper is to develop a 3- finger gripper and to analyze its finger with ANSYS software. A design study has been carried out for better understanding of geometrical influence on gripper functionality and performance. Directional deformation and maximum reaction moment are measured under axial and vertical loading conditions for the four metal combinations examined, and the performance is evaluated to determine the optimal material for a gripper. The findings could aid in getting desired results for specific grabbing applications, whose outcomes may lead to the creation of an application specific gripper.
Keywords Analysis in grasping, 3-finger robotic gripper, stress in gripper, end effector for manipulator, deformation
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INTRODUCTION
In todays modern industrial need a gripper becomes a vital element for handling components. A gripper is so chosen based on the material to be handled and its properties. With the development in technologies, in todays world choosing a gripper for a pick and place application has become a lot easier and a wide variety of actuation technique has been developed and incorporated inside a gripper. Choosing a gripper is always a key factor for any repeated application. For any gripper to function effectively, its end application along with the work environment parameters has to be kept in mind while designing the gripper and specifications has to be drawn accordingly so as to enable the gripper to adapt with the user needs and to work effectively without the application deviation. The sensing and control feature boosts the capability of a gripper by making it more adaptive to the work material it is going to make contact with in order to avoid damaging the material as well the gripper itself.
A gripper acts as an interactive medium [1] between the robotic arm and the element to be picked. To enable this interaction to happen in a smooth manner intelligent, efficient and adaptive grippers must be designed which has to be
flexible yet effective in accomplishing the picking task in an industrial environment. A soft two-finger robotic gripper [2] inspired by the human hand is being created with fabric with a maximum bending angle of 180 degrees to grasp a variety of methods and approaches for soft robotic gripping. A 3-finger 3D printed gripper [3] controlled with servo motor is designed and its grasping performance are analysed whose design can be replicated for research and educational purposes. A detailed evaluation [4] and comparison between vacuum gripper and a 3-finger gripper is made for choosing for warehousing picking and summarizes that both finds their unique application in different conditions and are based on the material to be picked. A soft adaptive origami inspired design [5] has been proposed utilizing 3-finger design for picking the objects. The 11-layer tower per finger design is cable driven and actuated by servo motors. The developed has vision-based autonomous control and evaluated with many fragile components of different size and shapes and revealed that the origami structure absorbed most of the excessive force during grasping. A mesoscopic gripper [6] is 3D printed and kinematic analysis on the gripper is made for enabling angled gripping by adapting the gripper fingertip to the shape of the object being grasped. With this novel approach, limitations of geometric constraint in picking of objects are reduced.
Contact pressure map based finite element analysis [7] is made with pressure sensing sheet to study the pressure points when picking household objects and fruits as well a stability analysis is carried out. A detailed analysis on precision grip force [8] has been carried out and compared with calculated theoretical value and experimentally measured values which results in validating the analysis. Optimal design for adaptive compliant gripper (ACG) [9] is presented for quick handling of materials with varied volume and pattern and soft-add topology optimization algorithm is carried out along with Finite element analysis is carried out to analyse the dynamic realization of the gripper. A 4-finger 16DOF gripper [10] is designed for efficient grasping and kinematic analysis is carried out to address the three major challenges namely, grasping, manipulation and releasing in desired posture. Finite Element Analysis is carried out on a 3-fingered microgripper [11] to analyse the force displacement and yield limit on the adjustable block to offset the fingers for enabling multi object gripping. A Finite Element-based grasp synthesis technique
[12] which discusses the disparity in wrench space analysis and evaluates for grasp stability by running several FE grasp simulations with various settings and identified as the most stable grasp. Simulation framework [13] for dynamic grasping conditions based on Finite Element method are evaluated and validated with Hertzian contact theory to obtain the stability of the grasp.Finite Element Analysis [14] and Finite Element Method [15], [16] are the most frequently used numerical techniques for evaluating material contact behaviour by constructing a contact situation with geometry, appropriate mechanical characteristics, and model parameters. Whenever the FE model is solved, the deformation, contact force, and region of engagement of forces on the test material are obtained. The study can be useful for selecting the optimal material on comparing the contact behaviour and validating them with experimental results.
Todays fast-moving world makes use of commercially available gripper for achieving the desired tasks. But the problem that arises is due to the limitations as in some cases the gripper will not be meant for the task that it is been used for. The motive of this paper is to develop a 3-finger gripper and to analyse its finger with the ANSYS software for four different metal alloys with axial and vertical loading conditions to acquire the directional deformation and maximum reaction moment along with stress distribution for selecting the optimum material for the gripper.
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MATERIALS AND METHODS
A. Selecting a Template (Heading 2)
A three-finger metal gripper along with the mounting extension arm for precision grasping applications as shown in Fig. 1 was modelled using SOLIDWORKS, and its fingers were analysed using the ANSYS software for four different metal alloys as finger material under axial and vertical loading circumstances to obtain the directional deformation and maximum reaction moment, as well as stress distribution using the Finite Element Analysis method [14][16]. Instead of analysing the gripper post fabrication ith pressure plates [7], it is analysed in the design level with ANSYS workbench. Wrench space formulations are frequently employed for acquiring the grip stability in dynamic circumstances, but the physical traits of the material being grasped are neglected since the formulations are predicated on static equilibrium calculations and the findings cannot be verified experimentally, hence a Finite Element based approach using ANSYS workbench is used in this paper.
Fig. 1. Designed 3-finger gripper with arm
The overall structure is designed in a way to keep it extremely lightweight and in the unactuated state it is retracted and fully folded. The stiffness of the fingers is so determined based on the material to be grasped and the force to be applied to lift the component with coefficient of friction. The gripper is designed and the dimensional details are elaborated in Fig. 2 which depicts the complete dimensions with arm.
Fig. 2. Dimensional details of the gripper with arm
Four peculiar materials namely stainless steel, magnesium alloy, titanium alloy and aluminium alloy are chosen for analysis and the conditions considered for the robotic arm is given in the Fig. 3. A load of 10Kg (100N) is enforced to the palm of the robotic arm. The analysis with respect to the influence of geometry on the bending angle and grasping strength are showcased in the experimental results section.
Fig. 3. Conditions for analysing the gripper
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RESULTS AND DISCUSSION
The designed model is analysed with the ANSYS software to obtain the stress results in different parts of the gripper and arm body. Stainless steel is chosen as the material for the entire analysis and the directional deformation on different parts of the arm are shown in Fig. 4. Fig. 5 shows the directional deformation at the finger joint plate.
Fig. 4. Stress acting on the arm part 1 to 4
Fig. 5. Stress concentration at gripper finger joint
The equivalent Von-Mises stress are obtained for the arm joints and are elaborated in the Fig. 6 and Fig. 7 picturizes the total deformation that has occurred in the arm and its joints respectively.
Fig. 6. Von-Mises Stress acting on the different parts of the arm
Fig. 7. Total deformation of the gripper with arm
Four different metals were taken for finger fabrication namely Stainless steel, Aluminium alloy, Magnesium alloy and Titanium alloy and the stress Vs change in area of cross section for the maximum equivalent stress for different material combinations are elucidated in the Fig. 8 under axial loading and Fig. 9 under vertical loading.
The maximum reaction moment for the links 1 to 4 is obtained for the four metal combinations during axial and vertical loading with a load of 100N and are plotted in the Fig. 10 and Fig. 11.
Fig. 8. Maximum equivalent stress under axial loading for different finger combinations
Fig. 9. Maximum equivalent stress under vertical loading for different finger combinations
Fig. 10. Maximum reaction moment at links 1 to 4 with axial loading of 100N
Fig. 11. Maximum reaction moment at links 1 to 4 with vertical loading of 100N
The directional deformation for the axial and vertical loading are as depicted in the Fig. 12 and Fig. 13 at an applied force of 100N.
Fig. 12. Axial Directional deformation at applied force of 100N
Fig. 13. Vertical Directional deformation at applied force of 100N
Tables 1 and 2 illustrate the stress, deformation, and reaction moment under axial and vertical loading situations and conditions with a 100N applied load on the four metal combinations chosen for the designed gripper model. The robotic arm is modelled in Solidworks and analysed with ANSYS workbench software under axial and vertical loading conditions with a 100N load for all the four different metal combinations. There is a decrease in stress and deformation as the cross-sectional area of the link increases and Magnesium alloy displays reduced variance in the stress value from 2.560 to 2.14Mpa. Under vertical loading conditions, all four metal combinations indicate a comparable range of stress levels. When comparing the links for directional deformation, link 1 experiences the most deformation in axial loading, whereas link 4 experiences the most deformation in vertical loading. When the maximal reaction moment from the trend is considered, the link 2 exhibits greater deviations under axial and vertical loading circumstances. The results clearly reveal that the Magnesium alloy outperforms the other three metal combinations in terms of directional deformation and maximal deformation under axial and vertical loading circumstances, proving it to be more suited for the robotic gripper finger in industrial environment.
TABLE I. RESULTS ON VARIOUS METAL COMBINATIONS UNDER AXIAL LOADING CONDITIONS
Material
Description
Mass (Kg)
Axial Load (100 N)
Maximu m Equivalen t Stress (Mpa)
Maximum Deformation (m)
Directional Deformation (-Y Axis)
Maximum Reaction Moment
Link 1
Link 2
Link 3
Link 4
Link 1
Link 2
Link 3
Link 4
(m)
(N-m)
e-7
e-5
e-4
e-4
Stainless steel
10
mm
32.165
10.102
0.004558
1.42
2.26
1.00
1.21
8.55
470.03
26.14
1.04
15
mm
40.395
8.5871
0.00394
2.13
1.94
0.87
1.05
9.16
803.25
26.04
0.87
20
mm
43.485
9.2037
0.004229
2.35
2.02
0.93
1.12
9.22
902.80
27.99
1.01
25
mm
45.892
8.9536
0.004067
2.41
1.82
0.89
1.08
9.38
661.31
30.25
0.98
Solid
49.872
8.7533
0.003971
2.61
1.81
0.81
1.06
9.47
489.58
27.47
1.01
Aluminium alloy
10
mm
11.496
3.8073
0.001708
1.40
2.26
1.01
1.24
3.4951
172.1
9.8394
0.48204
15
mm
14.438
3.1924
0.001605
2.07
1.92
0.87
1.06
3.731
289.1
9.7869
0.42749
20
mm
15.542
3.4004
0.001564
2.31
1.99
0.93
1.13
3.7555
325.39
10.449
0.49066
25
mm
16.403
3.3103
0.001506
2.35
1.80
0.89
1.08
3.8148
237.02
11.294
0.4781
Solid
17.809
3.3218
0.001572
2.55
1.79
0.87
1.06
3.8494
178.13
10.298
0.48806
Magnesium alloy
10
mm
7.407
2.5633
0.03448
1.44
2.37
1.07
1.31
2.5113
113.95
6.7036
0.39307
15
mm
9.382
2.1238
0.032682
2.13
1.99
0.91
1.11
2.6742
188.2
6.6208
0.34133
20
mm
10.101
2.2531
0.033123
2.37
2.06
0.97
1.18
2.691
212.3
7.0118
0.38866
25
mm
10.659
2.1955
0.03271
2.41
1.87
0.92
1.13
2.7305
153.8
7.6101
0.37924
Solid
11.573
2.1406
0.032623
2.61
1.86
0.90
1.11
2.755
117.6
6.9464
0.38702
Titanium alloy
10
mm
19.174
5.894
0.004175
1.69
2.71
1.19
1.45
5.3716
281.07
16.006
0.68091
15
mm
24.08
4.9138
0.003796
2.52
2.29
1.02
1.24
5.7501
467.77
15.82
0.58755
20
mm
25.923
5.2484
0.003932
2.79
2.38
1.09
1.33
5.7932
529.74
16.934
0.67775
25
mm
27.357
5.1181
0.003839
2.85
2.17
1.05
1.28
5.8883
384.17
18.542
0.65817
Solid
29.703
4.9927
0.003781
3.09
2.15
1.03
1.25
5.9427
296.37
16.703
0.67348
TABLE II. RESULTS ON VARIOUS METAL COMBINATIONS UNDER VERTICAL LOADING CONDITIONS
Material
Description
Mass (Kg)
Vertical Load (100 N)
Maximu m Equivalen t Stress (Mpa)
Maximum Deformation (m)
Directional Deformation (-Y Axis)
Maximum Reaction Moment
Link 1
Link 2
Link 3
Link 4
Link 1
Link 2
Link 3
Link 4
(m)
(N-m)
e-7
e-5
e-4
e-4
Stainless steel
10
mm
32.165
31.287
0.013258
3.01
5.98
2.91
3.57
78.437
1160.3
83.507
4.5093
15
mm
40.395
23.051
0.009807
3.82
4.29
2.16
2.66
75.61
1657.8
71.688
3.8922
20
mm
43.485
23.695
0.010127
4.03
4.28
2.21
2.72
74.461
1769.3
74.097
4.3155
25
mm
45.892
22.673
0.009569
4.01
3.79
2.08
2.57
74.105
1257.1
77.968
4.1783
Solid
49.872
21.839
0.009177
4.60
3.66
2.00
1.80
74.109
893.36
69.759
4.286
Aluminium alloy
10
mm
11.496
24.522
0.010117
5.69
12.33
6.15
7.60
73.39
860.89
67.405
3.952
15
mm
14.438
17.306
0.007147
6.65
8.26
4.33
5.36
70.19
1131.1
55.483
3.4506
20
mm
15.542
17.531
0.007251
6.83
8.09
4.38
5.42
69.002
1185.6
56.553
3.7788
25
mm
16.403
16.696
0.006804
6.68
7.10
4.08
5.08
68.544
826.14
59.297
3.6559
Solid
17.809
15.989
0.006498
6.85
6.79
3.90
4.85
68.499
583.36
52.695
3.7543
Magnesium alloy
10
mm
7.407
22.789
0.12885
8.16
18.15
9.10
11.25
72.408
800.57
64.397
3.8283
15
mm
9.382
15.861
0.097551
9.30
11.89
6.29
7.81
69.138
1023.8
52.259
3.3503
20
mm
10.101
16.004
0.096597
9.47
11.58
6.34
7.87
67.946
1064.7
53.086
3.6523
25
mm
10.659
15.234
0.091988
9.19
10.15
5.91
7.37
67.466
735.42
55.875
3.5291
Solid
11.573
14.555
0.089373
9.34
9.68
5.62
7.02
67.413
524.48
49.403
3.6289
Titanium
10
mm
19.174
25.821
0.01309
4.82
10.07
4.94
6.08
75.268
966.27
73.776
4.1234
15
24.08
18.454
0.00973
5.87
6.91
3.53
4.36
72.216
1297.6
61.466
3.5819
mm
20
mm
25.923
18.802
0.00993
6.11
6.82
3.59
4.44
71.053
1377.8
62.964
3.9249
25
mm
27.357
17.976
0.00945
6.01
6.03
3.37
4.18
70.627
961.67
66.933
3.7891
Solid
29.703
17.228
0.00909
6.23
5.81
3.22
4.00
70.604
704.17
59.17
3.8989
-
CONCLUSION
A design study has been carried out for better understanding of geometrical influence on gripper functionality and performance. Four different metal alloy combinations were taken for research and the evidence is picturized and briefly discussed. The results clearly show that the Magnesium alloy surpasses the other three metal combinations in terms of directional deformation and maximal deformation under axial and vertical loading conditions, demonstrating its suitability for the robotic gripper finger. The findings could aid in getting desired results for specific grabbing applications.
In the future, more research exploration will be exacted to identify additional administration indicators, namely introducing a force torque sensor to quantify the strain in the material being gripped. The outcomes of the experiments findings may lead to the creation of an application specific gripper that can be used for a variety of grasping and manipulation tasks. Operational and economic aspects have to be placed with equal priority when designing a gripper for an application specific task.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
ACKNOWLEDGMENT
We thank our colleagues from Department of Mechanical Engineering, Sri Venkateswara College of Engineering who provided insight and expertise that greatly assisted in the research and the department for offering ANSYS workbench to conduct the research.
AUTHOR BIOGRAPHY
Prashanna Rangan R is now a master candidate in Department of Industrial Automation and Robotics, Sri Venkateswara College of Engineering, India, email: prashanna098@gmail.com. He received his Bachelors degree in Mechatronics engineering from Kongu Engineering College, India in 2019. His research area includes, Robotics, Human assistive devices, PLC automation, Machine Vision system and IoT. He has published his Research findings in 11 International Journals. He has presented his research findings in 9 International and 5 National Conferences.
Nithish K is now an undergraduate candidate in Department of Mechanical Engineering, Sri Venkateswara College of Engineering, India. His research area includes Artificial Intelligence, Robotics, Automation and IoT. He has presented his findings in 2 National Conferences.
Vishnu Chandran R is now a master candidate in Department of Industrial Automation and Robotics, Sri Venkateswara College of Engineering, India. He received his
Bachelors degree in Mechanical engineering from Panimalar Institute of Technology, India in 2020. His research area includes, Automation, Robotics, Hydraulics and Pneumatics system. He has presented his findings in 1 National Conference.
Arul Kumar M is currently Assistant professor in Department of Mechanical Engineering, Sri Venkateswara College of Engineering, India. He received his Masters degree in Computer Aided Design from Sri Venkateswara College of Engineering, India in 2013. His research area includes CAD, Mechatronics, Robotics, Composite Materials. He has published his Research findings in 4 International Journals. He has presented his research findings in 10 International/National Conferences.
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