A design method based on genetic algorithms for optimizing the dosing device of a robot for aliquoting biological samples

A design method based on genetic algorithms for optimizing the dosing device of a robot for aliquoting biological samples

Larisa A. Rybak
Doctor of Engineering Sciences, Professor, Head of Laboratory, Belgorod State Technological University named after V.G. Shukhov (BSTU named after V.G. Shukhov), Research Laboratory of Robotics and Control Systems, 46, ul. Kostyukova, Belgorod, 308012, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0002-8856-7823

Giuseppe Carbone
PhD, University of Calabria, Department of Mechanical, Energy and Management Engineering, Via Pietro Bucci, Rende, 87036, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0003-0831-8358

Dmitry I. Malyshev
Junior Research Scientist, BSTU named after V.G. Shukhov, Research Laboratory of Robotics and Control Systems, 46, ul. Kostyukova, Belgorod, 308012, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0002-6059-9102

Vladislav V. Cherkasov
Research Engineer, BSTU named after V.G. Shukhov, Research Laboratory of Robotics and Control Systems, 46, ul. Kostyukova, Belgorod, 308012, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0002-6733-3817

UDC identifier: 62-529.4::621.039.7

EDN: IDDQWK

Abstract. The article presents the development and optimization of a dosing device for a robotic system designed for aliquoting biological samples. Existing automated liquid dosing systems are usually integrated into robotic systems, and are not intended for use in other systems. The article proposes a new technical solution: a modular dosing device compatible with various manipulators. A mathematical model of the device was developed and its multi-criteria optimization was carried out using genetic algorithms, which made it possible to select key parameters that affect the accuracy and speed of dosing, taking into account the minimization of dimensions and weight. The process of creating and testing an experimental sample of a dosing device is also described. The results obtained showed the effectiveness of the proposed design methods and the versatility of the approach. The experimental sample tested in laboratory conditions proved the effectiveness and operability of the proposed design, as well as the ability to perform accurate and fast processing of biological samples. The developed device can also be used in various fields requiring accurate and fast dosing of liquids, which opens up new prospects for its use in industry and medicine.

Key words: dosing device, manipulator equipment, multi-criteria optimization, genetic algorithms, aliquoting, biological samples

For citation: Rybak, L.A., Carbone, G., Malyshev, D.I. and Cherkasov, V.V. (2025), "A design method based on genetic algorithms for optimizing the dosing device of a robot for aliquoting biological samples", Robotics and Technical Cybernetics, vol. 13, no. 4, pp. 259-267, EDN: POZVMB. (in Russian).

Acknowledgements
The work was supported by the state task of the Ministry of Science and Higher Education of the Russian Federation under the grant FZVN-2020-0017. The work was realized using equipment based of High Technology Center at BSTU named after V. G. Shukhov.

References

  1. National Cancer Institute. Biorepositories and Biospecimen Research Branch National Institutes of Health Table of Contents. National Cancer Institute (2016), “NCI Best Practices for Biospecimen Resources”, available at: URL: https://www.juntadeandalucia.es/salud/biobanco/sites/default/files/users/user29/2016-ncibestpractices.pdf (Accessed 6 November 2025).
  2. Houriiyah, T., San, J., Jennifer, G. and Tulio, O. (2020), “Unlocking the efficiency of genomics laboratories with robotic liquid-handling”, BMC Genomics, 21, no. 1, 729, DOI: 10.1186/s12864-020-07137-1
  3. Philip, D., Tobias, K., Geethika, A., Nouraiz, A., Yang, Z. et al. (2022), “Open-source personal pipetting robots with live-cell incubation and microscopy compatibility”, Nature Communications, vol. 13, no. 1, 2999, DOI: 1038/s41467-022-30643-7
  4. Naruki, Y., Kourosh, D., Mohammad, V., Animesh, G. and Alán, A. (2023), “Digital pipette: open hardware for liquid transfer in self-driving laboratories”, Digital Discovery, 2, no. 6, pp. 1745-1751, DOI: 10.1039/D3DD00115F
  5. Thurow, K. and Junginger, S. (2022), “Devices and Systems for Laboratory Automation”, , India: Wiley-VCH Chennai, p. 498.
  6. Ji Yeong, N., Sun-Woo, Y., Youngji, K., Thi, L., et al. (2019), “Pipetting-based immunoassay for point-of-care testing: Application for detection of the influenza A virus”, Scientific Reports, 9, no. 1, 16661, DOI: 10.1038/s41598-019-53083-8
  7. Haack, C., Engel, T. and Holenstein, T. (2014), Pipetting device, modular pipetting unit, pipetting system and method for pipetting of fluid samples, United States, Pat. № US 8900878 B2.
  8. Xin, Y., Xiaojie, W., Baoqing, L. and Jiaru, C. (2023), “A high-precision automated liquid pipetting device with an interchangeable tip”, Rev Sci Instrum., vol. 94, no. 9, 094102, DOI: 10.1063/5.0139565
  9. Hojin, K., In Ho, C., Sanghyun, L., Seungbum, B. and Joonwon, K. (2015), “Plug-in nanoliter pneumatic liquid dispenser with nozzle design flexibility”, Biomicrofluidics, vol. 9, no. 6, 064102, DOI: 1063/1.4935937
  10. Yuxin, M., Yang, P., Xuan, L., Baoqing, L. et al. (2018), “High-Precision Digital Droplet Pipetting Enabled by Plug-and-Play Microfluidic Pipetting Chip”, Lab on a Chip, vol. 18, no. 18, pp. 2720-2729, DOI: 1039/C8LC00505B
  11. Azim, P., Oriol, Y., William, J., Johan, R. et al. (2023), “3D-printed capillaric ELISA-on-a-chip with aliquoting”, Lab on a Chip, vol. 23, pp. 1547-1560, DOI: 1039/D2LC00878E
  12. Aitor, B., Jorge, E., Vanessa, C., Elena, D. et al. (2015), “Self corrected aliquoting method by overpressure for qPCR multiplexing”, In Proceeding of the 19th International Conference on Miniaturized Systems for Chemistry and Life Sciences (TAS 2015), Gyeongju (Korea), October, pp. 1353-1355.

Received 09.07.2025
Revised 25.08.2025
Accepted 13.10.2025