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Design and Development of an Adaptive Robotic Gripper

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In this paper, the design and development of an adaptive gripper are presented. Adaptive grippers are useful for grasping objects of varied geometric shapes by wrapping fingers around the object. The finger closing sequence in adaptive grippers may lead to ejection of the object from the gripper due to any unbalanced grasping force and such grasp failure is common for lightweight objects. Designing of the proposed gripper is focused on ensuring a stable grasp on a wide variety of objects, especially, lightweight objects (e.g., empty plastic bottles). The proposed actuation mechanism is based on movable pulleys and tendon wires which ensure that once a link stops moving, the other links continue to move and wrap around the object. Further, optimisation is used to improve the design of the adaptive gripper and the optimised gripper has been developed using 3D printing. Finally, validation is done by executing object grasping on common household objects using an industrial robot fitted with the developed gripper.

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References

  1. Piazza, C., Grioli, G., Catalano, M.G., Bicchi, A.: A Century of Robotic Hands. Annu. Rev. Control Robot. Auton. Syst. 2(1), 1–32 (2019). https://doi.org/10.1146/annurev-control-060117-105003

    Article  Google Scholar 

  2. Birglen, L., Gosselin, C.M.: Force Analysis of Connected Differential Mechanisms: Application to Grasping. Int. J. Robot. Res. 25(10), 1033–1046 (2006). https://doi.org/10.1177/0278364906068942

    Article  Google Scholar 

  3. Hirose, S.: Connected differential mechanism and its applications. In International Conference on Advanced Robotics, pp. 319–325 (1985)

  4. Luo, M., Mei, T., Wang, X., Yu, Y.: Grasp characteristics of an underactuated robot hand. In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04. 2004, New Orleans, LA, USA: IEEE, vol. 3, pp. 2236–2241 (2004). https://doi.org/10.1109/ROBOT.2004.1307394

  5. Rakić, M.: Multifingered robot hand with selfadaptability. Robot. Comput.-Integr. Manuf. 5(2–3), 269–276 (1989). https://doi.org/10.1016/0736-5845(89)90074-4

    Article  Google Scholar 

  6. Crowder, R.M.: An anthropomorphic robotic end effector. Robot. Auton. Syst. 7(4), 253–268 (1991). https://doi.org/10.1016/0921-8890(91)90057-R

    Article  Google Scholar 

  7. Kontoudis, G. P., Liarokapis, M., Vamvoudakis, K. G.: An Adaptive, Humanlike Robot Hand with Selective Interdigitation: Towards Robust Grasping and Dexterous, In-Hand Manipulation. In 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), Toronto, ON, Canada: IEEE, pp. 251–258 (2019). https://doi.org/10.1109/Humanoids43949.2019.9035037

  8. Zhang, Y., et al.: Design and control of the BUAA four-fingered hand. In Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), Seoul, South Korea: IEEE, pp. 2517–2522 (2001). https://doi.org/10.1109/ROBOT.2001.933001

  9. Townsend, W.: The BarrettHand grasper – programmably flexible part handling and assembly. Ind. Robot Int. J. 27(3), 181–188 (2000). https://doi.org/10.1108/01439910010371597

    Article  Google Scholar 

  10. Tamamoto, T., Koganezawa, K.: Multi-joint gripper with differential gear chain. In 2013 IEEE International Conference on Mechatronics and Automation, Takamatsu, Kagawa, Japan: IEEE, pp. 30–35 (2013). https://doi.org/10.1109/ICMA.2013.6617889

  11. Lovchik, C. S., Diftler, M. A.: The Robonaut hand: a dexterous robot hand for space. In Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), Detroit, MI, USA: IEEE, pp. 907–912 (1999). https://doi.org/10.1109/ROBOT.1999.772420

  12. Birglen L, Gosselin C, Laliberté T.: Underactuated robotic hands. in Springer tracts in advanced robotics, no. volume 40. Berlin: Springer (2008). https://doi.org/10.1007/978-3-540-77459-4

  13. Kashef, S.R., Amini, S., Akbarzadeh, A.: Robotic hand: A review on linkage-driven finger mechanisms of prosthetic hands and evaluation of the performance criteria. Mech. Mach. Theory. 145, 103677 (2020). https://doi.org/10.1016/j.mechmachtheory.2019.103677

    Article  Google Scholar 

  14. Lalibert ́, T., Gosselin, C. M.: Underactuation in Space Robotic Hands. In International Symposium on Artificial Intelligence and Robotics & Automation in Space, pp. 1–8 (2001)

  15. Yang, D., et al.: An anthropomorphic robot hand developed based on underactuated mechanism and controlled by EMG signals. J. Bionic Eng. 6(3), 255–263 (2009). https://doi.org/10.1016/S1672-6529(08)60119-5

    Article  Google Scholar 

  16. Jin, J., Zhang, W., Sun, Z., Chen, Q.: LISA Hand: Indirect self-adaptive robotic hand for robust grasping and simplicity. In 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guangzhou, China: IEEE, pp. 2393–2398 (2012). https://doi.org/10.1109/ROBIO.2012.6491328

  17. Cheng, M., Jiang, L., Ni, F., Fan, S., Liu, Y., Liu, H.: Design of a highly integrated underactuated finger towards prosthetic hand. In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Munich, Germany: IEEE, pp. 1035–1040 (2017). https://doi.org/10.1109/AIM.2017.8014155

  18. Li, X., Huang, Q., Chen, X., Yu, Z., Zhu, J., Han, J.: A novel under-actuated bionic hand and its grasping stability analysis. Adv. Mech. Eng. 9(2), 168781401668885 (2017). https://doi.org/10.1177/1687814016688859

    Article  Google Scholar 

  19. Hirose, S., Umetani, Y.: The development of soft gripper for the versatile robot hand. Mech. Mach. Theory. 13(3), 351–359 (1978). https://doi.org/10.1016/0094-114X(78)90059-9

    Article  Google Scholar 

  20. Kaneko, M., Higashimori, M., Takenaka, R., Namiki, A., Ishikawa, M.: The 100 G capturing robot - too fast to see. IEEEASME Trans. Mechatron. 8(1), 37–44 (2003). https://doi.org/10.1109/TMECH.2003.809137

    Article  Google Scholar 

  21. Massa, B., Roccella, S., Carrozza, M. C., Dario P.: Design and development of an underactuated prosthetic hand. In Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), Washington, DC, USA: IEEE, pp. 3374–3379 (2002). https://doi.org/10.1109/ROBOT.2002.1014232

  22. Carrozza, M.C., et al.: The SPRING Hand: Development of a Self-Adaptive Prosthesis for Restoring Natural Grasping. Auton. Robots. 16(2), 125–141 (2004). https://doi.org/10.1023/B:AURO.0000016863.48502.98

    Article  Google Scholar 

  23. Gosselin, C., Pelletier, F., Laliberte T.: An anthropomorphic underactuated robotic hand with 15 dofs and a single actuator. In 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA: IEEE, pp. 749–754 (2008). https://doi.org/10.1109/ROBOT.2008.4543295

  24. Ciocarlie, M., et al.: The Velo gripper: A versatile single-actuator design for enveloping, parallel and fingertip grasps. Int. J. Robot. Res. 33(5), 753–767 (2014). https://doi.org/10.1177/0278364913519148

    Article  Google Scholar 

  25. Sainul I. A., Deb, S., Deb, A. K.: A three finger tendon driven robotic hand design and its kinematics model, in CAD/CAM, robotics and factories of the future, D. K. Mandal and C. S. Syan, Eds., in Lecture Notes in Mechanical Engineering. New Delhi: Springer India, pp. 313–321 (2016). https://doi.org/10.1007/978-81-322-2740-3_30

  26. Ozawa, R., Tahara, K.: Grasp and dexterous manipulation of multi-fingered robotic hands: a review from a control view point. Adv. Robot. 31(19–20), 1030–1050 (2017). https://doi.org/10.1080/01691864.2017.1365011

    Article  Google Scholar 

  27. Stojanovic, V., Nedic, N.: Joint state and parameter robust estimation of stochastic nonlinear systems. Int. J. Robust Nonlinear Control. 26(14), 3058–3074 (2016). https://doi.org/10.1002/rnc.3490

    Article  MathSciNet  MATH  Google Scholar 

  28. Birglen, L., Gosselin, C.M.: Geometric Design of Three-Phalanx Underactuated Fingers. J. Mech. Des. 128(2), 356–364 (2006). https://doi.org/10.1115/1.2159029

    Article  MATH  Google Scholar 

  29. Ozawa, R., Hashirii, K., Yoshimura, Y., Moriya, M., Kobayashi, H.: Design and control of a three-fingered tendon-driven robotic hand with active and passive tendons. Auton. Robots. 36(1–2), 67–78 (2014). https://doi.org/10.1007/s10514-013-9362-z

    Article  Google Scholar 

  30. Ferrari, C., Canny, J.: Planning optimal grasps. In Proceedings 1992 IEEE International Conference on Robotics and Automation, Nice, France: IEEE Comput. Soc. Press, pp. 2290–2295 (1992). https://doi.org/10.1109/ROBOT.1992.219918

  31. Ciocarlie, M., Allen, P.: Data-driven optimization for underactuated robotic hands. In 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK: IEEE, pp. 1292–1299 (2010). https://doi.org/10.1109/ROBOT.2010.5509793

  32. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science. 220(4598), 671–680 (1983). https://doi.org/10.1126/science.220.4598.671

    Article  MathSciNet  MATH  Google Scholar 

  33. Coleman, T.F., Li, Y.: A Reflective Newton Method for Minimizing a Quadratic Function Subject to Bounds on Some of the Variables. SIAM J. Optim. 6(4), 1040–1058 (1996). https://doi.org/10.1137/S1052623494240456

    Article  MathSciNet  MATH  Google Scholar 

  34. Shilane, P., Min, P., Kazhdan, M., Funkhouser, T.: The princeton shape benchmark. In Proceedings Shape Modeling Applications, 2004., Genova, Italy: IEEE, pp. 167–388 (2004). https://doi.org/10.1109/SMI.2004.1314504

  35. Kasper, A., Xue, Z., Dillmann, R.: The KIT object models database: An object model database for object recognition, localization and manipulation in service robotics. Int. J. Robot. Res. 31(8), 927–934 (2012). https://doi.org/10.1177/0278364912445831

    Article  Google Scholar 

  36. Ansary, S.I., Deb, S., Deb, A.K.: A novel object slicing-based grasp planner for unknown 3D objects. Intell. Serv. Robot. 15(1), 9–26 (2022). https://doi.org/10.1007/s11370-021-00397-0

    Article  Google Scholar 

  37. Miller, A. T., Allen, P. K.: Examples of 3D grasp quality computations. In Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), Detroit, MI, USA: IEEE, pp. 1240–1246 (1999). https://doi.org/10.1109/ROBOT.1999.772531

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All the authors have contributed to the conception and overall design of the article. The design and development of the gripper, experiments, and analysis were carried out by [SI Ansary]. The first draft of the manuscript was prepared by [SI Ansary]. The project supervision and the manuscript review and editing were performed by [Sankha Deb] and [AK Deb]. All the authors read and approved the final manuscript.

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Correspondence to Sainul Islam Ansary.

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Appendix

Appendix

1.1 A. Kinematics of the Gripper

See Fig. 26

Fig. 26
figure 26

Kinematics schematic with parameter annotations and frame assignments for the two-finger gripper

The kinematics for the fingers is determined using the Denavit-Hartenberg (DH) notation. With the convention of DH frame assignments, the reference frames are attached to the links of the fingers, where the \(Z\)–axis of link frame coincides with the joint axis as shown in Fig. 26. The frames are denoted as [\({X}_{k}\) \({Y}_{k}\) \({Z}_{k}\)], where the subscript \(\{\mathrm{k}\}\) is the link number starting with \(\{k=0\}\) for the fixed knucle link. The DH parameters for both the fingers are given in Table

Table 2 DH parameters for both fingers of the two-finger gripper

2, where the four DH parameters denoted as \({\mathrm{\alpha }}_{\mathrm{k}-1}\), \({\mathrm{a}}_{\mathrm{k}-1}\), \({\mathrm{d}}_{\mathrm{k}}\) and \({\uptheta }_{\mathrm{k}}\) are for the interconnection between link \(k-1\) and link\(k\).

The forward kinematics relationship between frame \(\{0\}\) and the fingertip frame {3} is determined by using the DH parameters given in Table 2 as follows.

$${}_{3}{}^{0}T=\left[\begin{array}{cc}\begin{array}{cc}{r}_{11}& {r}_{12}\\ {r}_{21}& {r}_{22}\end{array}& \begin{array}{cc}{ r}_{13}& { p}_{x}\\ {r}_{23}& {p}_{y}\end{array}\\ \begin{array}{cc}{r}_{31}& {r}_{32}\\ 0& 0\end{array}& \begin{array}{cc}{ r}_{33} & {p}_{z}\\ 0& 1\end{array}\end{array}\right]$$
(29)

where, the matrix elements for the finger (F1) are as follows

$${p}_{x}= \mathrm{cos}\left({q}_{11}+{q}_{12}\right){L}_{3}-\mathrm{sin}({q}_{11}+{q}_{12}){D}_{3}+\mathrm{cos}\left({q}_{11}\right){L}_{1}+{L}_{0}$$
$${p}_{y}= 0$$
$${p}_{z}= \mathrm{sin}\left({q}_{11}+{q}_{12}\right){L}_{3}+\mathrm{cos}({q}_{11}+{q}_{12}){D}_{3}+\mathrm{sin}\left({q}_{11}\right){L}_{1}$$
$${r}_{11}= \mathrm{cos}({q}_{11}+{q}_{12})$$
$${r}_{13}= -\mathrm{sin}({q}_{11}+{q}_{12})$$
$${r}_{31}= \mathrm{sin}({q}_{11}+{q}_{12})$$
$${r}_{33}= \mathrm{cos}({q}_{11}+{q}_{12})$$
$${r}_{22}=1$$
$${r}_{12}={r}_{21}={r}_{23}={r}_{32}=0$$

1.2 B. Grasp Quality Metric

Here, a brief formulation is given to find the grasp quality while more details can be best found in [37]. The contact friction is modelled by approximating the friction cones with eight-sided pyramids having a unit length and a half angle of \({tan}^{-1}{\mu }_{s}\), where \({\mu }_{s}\) is the static friction coefficient as shown in Fig. 

Fig. 27
figure 27

Approximation of the friction cone with an eight-sided pyramid

27.

Then the contact force \({\varvec{f}}\) transfer to the object through contact is the linear combination of the vectors used to approximate the eight sides of the pyramid.

$${\varvec{f}}={\sum }_{j}^{m}{\alpha }_{j}{{\varvec{f}}}_{j}$$
(30)

where, \({\alpha }_{j}>0 , {\sum }_{j}^{m}{\alpha }_{j}=1\) and number of sides of the pyramid \(m=8\)

The contact wrench can be defined as the six-dimensional vectors formed by contact forces and torques at the contact point and is given as follows.

$${{\varvec{w}}}_{i,j}=\left(\begin{array}{c}{{\varvec{f}}}_{i,j}\\ \lambda ({{\varvec{d}}}_{i}\times {{\varvec{f}}}_{i,j})\end{array}\right)$$
(31)

where, \({{\varvec{f}}}_{i,j}\) is the \(j\)-th component of the friction cone at the \(i\)-th point of contact. \({{\varvec{d}}}_{i}\) is the distance vector from torque origin to the \(i\)-th point of contact. The scalar \(\lambda\) enforces the constraint \(\Vert {\varvec{\tau}}\Vert \le \Vert {\varvec{f}}\Vert\).

Now, assembling all the contact wrenches gives the convex hull or the polygon as follows.

$$W=ConvexHull\left({\bigcup }_{i}^{n}\{{{\varvec{w}}}_{i,1}, {{\varvec{w}}}_{i,2},\dots ..,{{\varvec{w}}}_{i,m}\}\right)$$
(32)

The volume \(v\) of the hull gives an invariant measure of grasp quality subjected to the origin of the wrench space lies within the convex hull. This quality measure is used as a basis for the optimisation of the link dimensions.

1.3 C. Design of Position-Based Impedance Controller

Grasping task involves a physical interaction between the finger and the object. Impedance control is preferred for a task that involves physical contact with the environment. Position-based impedance control can regulate positions and contact forces by regulating the dynamic behaviour of the system as a whole. The independent control of the two joints is not possible due to underactuated nature of the system. Here, the joints of the finger are controlled in joint space. The impedance controller is designed on top of a PID block as shown in Fig. 

Fig. 28
figure 28

Block diagram of the position-based impedance controller for the gripper

28.

Let \({\mathrm{q}}_{\mathrm{d}}\in {\mathrm{R}}^{\mathrm{n}}\) be the desired joint displacements. To achieve the desired joint trajectories and required torque for generating contact forces, the desired joint displacements are modified to a new set of joint displacement \({\mathrm{q}}_{\mathrm{s}}\in {\mathrm{R}}^{4}\). These modified displacements and actual joint displacements are used to compute displacement errors. The following PID feedback control law is used to generate the actuating torques.

$$\uptau ={\mathrm{K}}_{\mathrm{p}}\left({\mathrm{q}}_{\mathrm{s}}-\mathrm{q}\right)-{\mathrm{K}}_{\mathrm{v}}\dot{\mathrm{q}}+{\mathrm{K}}_{\mathrm{i}}\int \left({\mathrm{q}}_{\mathrm{s}}-\mathrm{q}\right)\mathrm{d\tau }$$
(33)

where\({\mathrm{K}}_{\mathrm{p}}\), \({\mathrm{K}}_{\mathrm{v}}\), \({\mathrm{K}}_{\mathrm{i}}\) are proportional, derivative and integral constants, respectively.

The modified joint displacements and the required joint displacements are related as follows.

$${\mathrm{q}}_{\mathrm{s}}={\mathrm{q}}_{\mathrm{d}}+{\uptau }_{\mathrm{c}}/{\mathrm{K}}_{\mathrm{s}}$$
(34)

where \({\mathrm{K}}_{\mathrm{s}}\) is the impedance stiffness.

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Ansary, S.I., Deb, S. & Deb, A.K. Design and Development of an Adaptive Robotic Gripper. J Intell Robot Syst 109, 13 (2023). https://doi.org/10.1007/s10846-023-01948-6

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