Abstract
We propose a computationally efficient approach for estimating sets of torques arising from inverse uncertain-dynamics of robot manipulators. Our proposed algorithm is based on the use of interval arithmetic computations within a recursive Newton-Euler algorithm for inverse dynamics. The set-based operations are here introduced considering uncertain dynamics parameters as well as uncertain linear/angular accelerations, and uncertain angular velocities of the base of the robot. We present numerical results that verify the tightness of the estimated torque sets and the computational efficiency of our proposed approach.
A. Giusti and C. Nainer—Contributed equally to this work.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Althoff, M., Giusti, A., Liu, S.B., Pereira, A.: Effortless creation of safe robots from modules through self-programming and self-verification. Sci. Robot. 4(31), eaaw1924 (2019)
Althoff, M., Grebenyuk, D.: Implementation of interval arithmetic in CORA 2016. In: Proceedings of the 3rd International Workshop on Applied Verification for Continuous and Hybrid Systems, pp. 91–105 (2016)
Brogårdh, T.: Robot control overview: an industrial perspective. MIC—Model. Identif. Control 30(3), 167 (2009)
De Luca, A., Ferrajoli, L.: A modified Newton-Euler method for dynamic computations in robot fault detection and control. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3359–3364 (2009)
Giusti, A., Althoff, M.: Efficient computation of interval-arithmetic-based robust controllers for rigid robots. In: 2017 1st IEEE International Conference on Robotic Computing (IRC), pp. 129–135 (2017)
Giusti, A., et al.: Flexible automation driven by demonstration: leveraging strategies that simplify robotics. IEEE Robot. Autom. Mag. 25(2), 18–27 (2018)
Haddadin, S., Albu-Schäffer, A., De Luca, A., Hirzinger, G.: Collision detection and reaction: a contribution to safe physical human-robot interaction. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, France, pp. 3356–3363, September 2008
Hollerbach, J.: Dynamic scaling of manipulator trajectories. ASME J. Dyn. Syst. Meas. Control 106, 102–106 (1984)
Moore, R.E., Kearfott, R.B., Cloud, M.J.: Introduction to Interval Analysis. Society for Industrial and Applied Mathematics, Philadelphia (2009)
Nainer, C., Giusti, A.: Automatically deployable robust control of modular reconfigurable robot manipulators. IEEE Robot. Autom. Lett. 7(2), 5286–5293 (2022)
Scalera, L., Vidoni, R., Giusti, A.: Optimal scaling of dynamic safety zones for collaborative robotics. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3822–3828 (2021)
Sciavicco, L., Siciliano, B., Villani, L.: Lagrange and Newton-Euler dynamic modelling of a gear-driven rigid robot manipulator with inclusion of motor inertia effects. Adv. Robot. 10(3), 317–334 (1996)
Wagner, M., Liu, S., Giusti, A., Althoff, M.: Interval-arithmetic-based trajectory scaling and collision detection for robots with uncertain dynamics. In: 2018 Second IEEE International Conference on Robotic Computing (IRC), pp. 41–48 (2018)
Acknowledgement
This work was supported by the Research Südtirol/Alto Adige grant for the project Reconfigurable Collaborative Agri-Robots (RECOARO) with CUP I52F20000300005. We would like to thank Simone Garbin for performing the measurements with the Clearpath Husky A200 at Fraunhofer Italia.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Giusti, A., Nainer, C. (2022). Inverse Uncertain-Dynamics of Robot Manipulators Using Interval Arithmetic. In: Niola, V., Gasparetto, A., Quaglia, G., Carbone, G. (eds) Advances in Italian Mechanism Science. IFToMM Italy 2022. Mechanisms and Machine Science, vol 122. Springer, Cham. https://doi.org/10.1007/978-3-031-10776-4_76
Download citation
DOI: https://doi.org/10.1007/978-3-031-10776-4_76
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-10775-7
Online ISBN: 978-3-031-10776-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)