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A Methodology for Benchmarking Force Control Algorithms

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Wearable Robotics: Challenges and Trends (WeRob 2020)

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 27))

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Abstract

Force control is nowadays a mature technology, widespread in modern robotics systems and commercialized within several application domains. However, assessing the performance of a force-controlled system is not a trivial task because it may be strongly influenced by the environment dynamics. Exerting a force on a soft environment is different from exerting a force on a rigid environment. Indeed, the same force-controlled robot can have different force responses in different environments and a standardized and comprehensive method to assess the performance of a force-controlled system is not available yet. This paper, as part of the Forecast project, aims at filling this gap by proposing a benchmarking method able to define a comprehensive score for a given force-controlled system accounting for its sensitivity to environment uncertainties and variations. This paper describes such benchmarking methodology which allows to compare force control algorithms on a common ground and to determine the preferable control solutions in a specific application domain.

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References

  1. R. Vicario, A methodology for benchmarking force control algorithms (2020). https://doi.org/10.13140/RG.2.2.18759.11680

  2. R. Muradore, A. Calanca, P. Fiorini, A review of algorithms for compliant control of stiff and fixed compliance robots. IEEE Trans. Mechatron. 21, 613–624 (2016)

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  3. Repository of SESim, http://www.gitlab.com/altairLab/elasticteam/SESim

  4. Repository of Forecast Control Framework, http://www.gitlab.com/altairLab/elasticteam/forecastnucleoframework

  5. Forecast UI showcase video, http://www.youtube.com/watch?v=40l8gGEEiSE

  6. Repository of Forecast UI, http://www.gitlab.com/altairLab/elasticteam/forecast/forecast-atlas

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Acknowledgements

The research has received funding from the European Union’s Horizon 2020 programme under grant agreement EUROBENCH n. 779963.

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Correspondence to R. Vicario .

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Vicario, R. et al. (2022). A Methodology for Benchmarking Force Control Algorithms. In: Moreno, J.C., Masood, J., Schneider, U., Maufroy, C., Pons, J.L. (eds) Wearable Robotics: Challenges and Trends. WeRob 2020. Biosystems & Biorobotics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-030-69547-7_99

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  • DOI: https://doi.org/10.1007/978-3-030-69547-7_99

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69546-0

  • Online ISBN: 978-3-030-69547-7

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