Control Algorithms for Motors of Anthropomorphic Gripping with Group Drive

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Problem statement: the current trend is the use in various spheres of human activity of service robots equipped with anthropomorphic grippers (AG) with the capabilities inherent in the human hand. The functionality of the AG is determined by the executive groups of links (IGZ) having a group drive with a variable structure. When enclosing an external object (VO), each opposed IGZ sequentially implements a contact with three output links. The algorithm for the simultaneous control of the motors must ensure that the position of the unsecured AO remains unchanged. Known AG control methods, for example impedance, do not provide this requirement. In addition, possible methods are focused on an unchanging control object, which is one output link of the IGZ. The variability of control objects, characteristic of systems with a group drive and a variable structure, determines the need for a fundamentally new approach to the control of engines of opposed IGZs. Methods used: theoretical research is based on the main provisions of the analysis of the functioning of complex systems, information processing that determines their state and decision-making based on them. The novelty of the proposed algorithms lies in the fact that the engine control is based on information about the interaction of the output links of both this IGZ and the opposite one. The sequence of switching on the motors is determined based on the analysis of changes in the set of conditions. External – the contact of the current control object with the VO, internal – an increase in the torque on the engine in comparison with the value that determines the free movement. This approach makes it possible, with only contact sensors on the output links, to implement adaptive control of the motors of the opposed IGZ. Result: The use of the proposed algorithms makes it possible to formalize the control of the motors of the opposed IGZ taking into account the position of the initially non-deterministic AO. Practical significance: the developed algorithms are designed to control anthropomorphic grips performing actions with the AO in unfavorable conditions for humans and the uncertainty of the AO position. Their use will increase the functionality of robots equipped with AG.

About the authors

Yulia I. Zhdanova

MIREA – Russian Technological University

Author for correspondence.
Email: zhdanova_yu@mirea.ru
ORCID iD: 0000-0002-3161-2646

senior lecturer, Department of Systems Engineering, Deputy Director at the Institute of Artificial Intelligence

Russian Federation, Moscow

Vladimir V. Moshkin

MIREA – Russian Technological University

Email: mvv56@inbox.ru
ORCID iD: 0000-0002-5421-5029

Cand. Sci., associate professor, Department of Systems Engineering

Russian Federation, Moscow

Mikhail P. Romanov

MIREA – Russian Technological University

Email: m_romanov@mirea.ru
ORCID iD: 0000-0003-3353-9945

Doct. Sci., Professor, Department of Control Problems, Director of the Institute of Artificial Intelligence

Russian Federation, Moscow

References

  1. Bogdanov А.А., Permyakov А.F., Zhdanova Yu.I. Synthesis of structural scheme of drive of adaptive multiple-link gripper. Zavalishin’s Readings. MATEC Web of Conferences. 2018. Vol. 161. Art. no. 03009. DOI: https://10.1051/matecconf/2018161030093.
  2. Billard A., Kragic D. Trends and challenges in robot manipulation. Science. 2019. Vol. 364. No. 6446.
  3. Zhdanova Yu.I. Algorithm for adaptive control of opposed executive systems with variable structure. Modern Science: Actual Problems of Theory and Practice. Series: Natural and Technical Sciences. 2021. No. 2. Pp. 51–57. (In Rus.)
  4. Zhdanova Yu.I., Moshkin V.V. Method of optimization synthesis of parameters of actuating system of anthropomorphic gripper with adaptive control. IOP Conference Series: Materials Science and Engineering. 2020. Vol. 971. No. 4. P. 042065.
  5. You W.S. et al. Design of a 3D-printable, robust anthropomorphic robot hand including intermetacarpal joints. Intelligent Service Robotics. 2019. Vol. 12. No. 1. Pp. 1–16.
  6. Golan Y., Shapiro A., Rimon E.D. A variable-structure robot hand that uses the environment to achieve general purpose grasps. IEEE Robotics and Automation Letters. 2020. Vol. 5. No. 3. Pp. 4804–4811.
  7. Kang L. et al. Design and Implementation of a Multi-Function Gripper for Grasping General Objects. Applied Sciences. 2019. Vol. 9. No. 24. P. 5266.
  8. Chu Z.Y. et al. Impedance identification using tactile sensing and its adaptation for an underactuated gripper manipulation. International Journal of Control, Automation and Systems. 2018. Vol. 16. No. 2. Pp. 868–875.
  9. Wang C. et al. Feature sensing and robotic grasping of objects with uncertain information: A review. Sensors. 2020. Vol. 20. No. 13. P. 3707.
  10. 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. Mechanism and Machine Theory. 2020. Vol. 145. P. 103677.
  11. Permyakov A.F., Bogdanov A.A., Zhdanova Yu.I. Adaptive drive of gripper links group. Patent 185794 the Russian Federation; IPC7 B25 J 15/08 Patent for a useful model 2018100908/02. 2018. Bul. 35.
  12. Huynh B.P., Kuo Y.L. Optimal fuzzy impedance control for a robot gripper using gradient descent iterative learning control in fuzzy rule base design. Applied Sciences. 2020. Vol. 10. No. 11. P. 3821.
  13. Raiola G. et al. Development of a safety-and energy-aware impedance controller for collaborative robots. IEEE Robotics and Automation Letters. 2018. Vol. 3. No. 2. Pp. 1237–1244.
  14. Park J., Choi Y. Input-to-state stability of variable impedance control for robotic manipulator. Applied Sciences. 2020. Vol. 10. No. 4. P. 1271.
  15. Erdemir G. Force transmission analysis of surface coating materials for multi-fingered robotic grippers. Peer J. Computer Science. 2021. Vol. 7. P. e401.
  16. Neha E. et al. Grasp analysis of a four-fingered robotic hand based on Matlab simmechanics. Journal of Computational & Applied Research in Mechanical Engineering (JCARME). 2020. Vol. 9. No. 2. Pp. 169–182.
  17. Salagor A.Yu., Stepanov I.V. Modern robotic demining complexes: foreign and domestic developments. In: Topical issues of improving tactical-special, fire and professional-applied physical training in the modern context of practical training for employees of internal affairs bodies: Collection workings of the International Scientific-practical Conference. St.-Petersburg: Published House of the St.-Petersburg University of the Ministry of Defense of the Russian Federation, 2019. С. 341–344.
  18. Huynh B.P., Kuo Y.L. Optimal fuzzy impedance control for a robot gripper using gradient descent iterative learning control in fuzzy rule base design. Applied Sciences. 2020. Vol. 10. No. 11. P. 3821.
  19. Li M. et al. Fuzzy impedance control of an electro-hydraulic actuator with an extended disturbance observer. Frontiers of Information Technology & Electronic Engineering. 2019. Vol. 20. No. 9. Pp. 1221–1233.

Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1. Block diagram of the main kinematic circuit (a) and the group drive diagram with dependent (t>), and with independent movements (c) of output links

Download (75KB)
3. Fig. 2. Brief record of the adaptive control scheme of the anthropomorphic gripper at the stage of retention: object parameters estimation, desired impedance model, underactuated gripper with grasper object

Download (149KB)
4. Fig- 3. Brief record of the scheme of the algorithm for identifying the position of an external object on a support

Download (410KB)
5. Fig. 4. Stages of grasping the output links of the surface of a stationary external object: a - the initial phase of the first stage; b - the transition to the second stage; c - the second stage; d - the transition to the third stage; e - the third stage; f- the completion of grasping

Download (157KB)
6. Fig. 5. Block diagram of the motor control algorithm of the oppositional executive groups of links at the stage of circumference of an external object not fixed on a support

Download (407KB)


This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies