Skip to main content

Research on Force Perception of Robot End-Effector Based on Dynamics Model

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13457))

Included in the following conference series:

Abstract

With the wide application of robots in the industrial field, higher requirements are put forward for the use of robots. The force information at the end of the robot is an important execution information of the robot, and the accuracy of its estimation accuracy directly affects the execution precision of the robot. Aiming at this problem, an accurate dynamic model of six-Dofs robot was established, and the torque changes under different working conditions in the process were analyzed. The dynamics simulation model of the robot was built by the co-simulation of MATLAB and Adams software. According to the collected torque information, it will be transformed into the end contact force information. The accuracy of estimating the end force can reach 98.6%.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wang, X.L., et al.: kinematics analysis and optimization design of NOVAL 4-DOF parallel mechanism. J. Northeastern Univ. (Nat. Sci.), 39(04), 532–537 (2018)

    Google Scholar 

  2. Leboutet, Q., et al.: Inertial parameter identification in robotics: a survey. Appl. Sci. 11(9), 4303 (2021)

    Article  Google Scholar 

  3. Urrea, C., Pascal, J.: Design, simulation, comparison and evaluation of parameter identification methods for an industrial robot. Comput. Electr. Eng. 67, 791–806 (2018)

    Article  Google Scholar 

  4. Gaz, C., et al.: Dynamic identification of the franka emika panda robot with retrieval of feasible parameters using penalty-based optimization. IEEE Robot. Autom. Lett. 4(4), 4147–4154 (2019)

    Article  Google Scholar 

  5. Yousri, D., et al.: Static and dynamic photovoltaic models’ parameters identification using chaotic heterogeneous comprehensive learning particle swarm optimizer variants. Energy Convers. Manag. 182, 546–563 (2019)

    Article  Google Scholar 

  6. Gründel, L., Reiners, C., Lienenlüke, L., Storms, S., Brecher, C., Bitterolf, D.: Frequency-based identification of the inertial parameters of an industrial robot. In: Behrens, B.-A., Brosius, A., Hintze, W., Ihlenfeldt, S., Wulfsberg, J.J. (eds.) Production at the leading edge of technology. LNPE, pp. 429–438. Springer, Heidelberg (2021). https://doi.org/10.1007/978-3-662-62138-7_43

    Chapter  Google Scholar 

  7. Kallu, K.D., et al.: Implementation of a TSMCSPO controller on a 3-dof hydraulic manipulator for position tracking and sensor-less force estimation. IEEE Access 7, 177035–177047 (2019)

    Article  Google Scholar 

  8. Changhong, G., et al.: Hybrid position/force control of 6-dof hydraulic parallel manipulator using force and vision. Indus. Robot Int. J. 43, 274–283 (2016)

    Article  Google Scholar 

  9. Li, Y.J., et al.: Research on a novel parallel spoke piezoelectric 6-DOF heavy force/torque sensor. Mech. Syst. Signal Process. 36(1), 152–167 (2013)

    Article  Google Scholar 

  10. Zeng, F., Xiao, J., Liu, H.: Force/torque sensorless compliant control strategy for assembly tasks using a 6-DOF collaborative robot. IEEE Access 7, 108795–108805 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ming Hu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yao, Z., Hu, M., Guo, Y., Wu, J., Yang, J. (2022). Research on Force Perception of Robot End-Effector Based on Dynamics Model. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13457. Springer, Cham. https://doi.org/10.1007/978-3-031-13835-5_55

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-13835-5_55

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13834-8

  • Online ISBN: 978-3-031-13835-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics