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Robust design for the lower extremity exoskeleton under a stochastic terrain by mimicking wolf pack behaviors

Zhonglai Wang*, Shui Yu, Leo Yi Chen, Yun Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

While kinematics analysis plays an important role in studying human limb motions, existing methods (namely, direct and inverse kinematics) have their deficiencies. To improve, this paper develops a robust design method using artificial intelligence and applies it to the lower extremity exoskeleton design under a stochastic terrain. An inverse kinematic model is first built considering the impact on human's comfort from the stochastic terrain. Then, a robust design model is constructed based on the inverse kinematic model, where the design framework mimics wolf pack behaviors and the robust design problem is thus solved for keeping probabilistic consistency between the exoskeleton and its wearer. A case study validates the effectiveness of the developed robust method and algorithm, which ensures walking comfort under the stochastic terrain within the validity of simulations.

Original languageEnglish
Pages (from-to)30714-30725
Number of pages12
JournalIEEE Access
Volume6
DOIs
Publication statusPublished - 18 May 2018

Funding

This work was supported in part by the National Natural Science Foundation of China under Contract 11472075, in part by the China Postdoctoral Science Foundation under Contract 2013T60838, and in part by the DGUT High-Level Talent Research Startup Grants under Contracts. G200906-14 and KCYXM2017012.

Keywords

  • inverse kinematics
  • lower extremity exoskeleton
  • robust design
  • stochastic terrain
  • wolf packs

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