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Towards Robust Physical Human Robot Interaction by an Adaptive Admittance Controller

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Abstract

The regular admittance controller cannot be easily transferred to the physical human–robot interaction scenario because of the dynamic stiffness of the human arm. The dynamic interaction of humans can cause high frequency and unsafe oscillation of the robot arm. Based on the adaptive control scheme, this paper presents an online sensory-based analytical approach to recognize and quantify the “stability index" named as a robust haptic observer. The observer performs the Fast Fourier Transform on the interaction force signal within a sliding window and quickly detects system oscillation through a simple mathematical transformation. Compared with the existing methods, it can calculate a normalized system stability index more accurately and faster. This quantified index is employed in a linearized adaptive law to tune the parameters of the admittance controller. Experimental validation of the proposed strategy is performed and compared with state-of-the-art work in a task of human-guided drawing. The results show that our proposed approach can effectively detect oscillation, and the drawing time is shortened by 15% with the same tracking accuracy. In addition, the energy consumption is 44.4% less on average.

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Data Availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Code Availability

The code during the current study is available from the corresponding author on reasonable request.

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Funding

This research was supported by the China Scholarship Council under Grant (202106080049), and in part by "DEXMAN" project (ID:LI 2811/1–1) funded by DFG, National Natural Science Foundation of China under Grant (NO.62273081).

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Author notes

  1. Guanghui Liu and Qiang Li contributed equally to this work.

Authors and Affiliations

  1. Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China

    Guanghui Liu & Lijin Fang

  2. Neuroinformatics Group & CITEC, Bielefeld University, Bielefeld, Germany

    Qiang Li

  3. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

    Hualiang Zhang

Authors
  1. Guanghui Liu
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  2. Qiang Li
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  3. Lijin Fang
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  4. Hualiang Zhang
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Contributions

Guanghui Liu—Conceptulization, Methdology, Software, Data curation, Writing-original draft. Qiang Li—Software, Data curation, Validation, Writing—review & editing. Lijin Fang—Supervision, Writing—review & editing. Hualiang Zhang—Supervision, Writing—review & editing.

Corresponding author

Correspondence to Lijin Fang.

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Liu, G., Li, Q., Fang, L. et al. Towards Robust Physical Human Robot Interaction by an Adaptive Admittance Controller. J Intell Robot Syst 109, 59 (2023). https://doi.org/10.1007/s10846-023-01999-9

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  • DOI: https://doi.org/10.1007/s10846-023-01999-9

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