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Mechanical Sciences An open-access journal for theoretical and applied mechanics
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Volume 8, issue 2
Mech. Sci., 8, 249-258, 2017
https://doi.org/10.5194/ms-8-249-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Mech. Sci., 8, 249-258, 2017
https://doi.org/10.5194/ms-8-249-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Aug 2017

Research article | 14 Aug 2017

Development of a lower extremity wearable exoskeleton with double compact elastic module: preliminary experiments

Yi Long1,2, Zhi-jiang Du1, Chao-feng Chen1, Wei-dong Wang1, and Wei Dong1 Yi Long et al.
  • 1State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
  • 2Zhongshan Torch Group, Co. Ltd, Zhongshan, China

Abstract. In this paper, a double compact elastic module is designed and implemented in the lower extremity exoskeleton. The double compact elastic module is composed of two parts, i.e., physical human robot interaction (pHRI) measurement and the elastic actuation system (EAS), which are called proximal elastic module (PEM) and distal elastic module (DEM) respectively. The PEM is used as the pHRI information collection device while the DEM is used as the compliance device. A novel compact parallelogram-like structure based torsional spring is designed and developed. An iterative finite element analysis (FEA) based optimization process was conducted to find the optimal parameters in the search space. In the PEM, the designed torsional spring has an outer circle with a diameter of 60mm and an inner hole with a diameter of 12mm, while in the DEM, the torsional spring has the outer circle with a diameter of 80mm and the inner circle with a diameter of 16mm. The torsional spring in the PEM has a thickness of 5mm and a weight of 60g, while that in the DEM has a thickness of 10mm and a weight of 80g. The double compact elastic module prototype is embedded in the mechanical joint directly. Calibration experiments were conducted on those two elastic modules to obtain the linear torque versus angle characteristic. The calibration experimental results show that this torsional spring in the PEM has a stiffness of 60.2Nmrad−1, which is capable of withstanding a maximum torque of 4Nm, while that in the DEM has a stiffness of 80.2Nmrad−1, which is capable of withstanding a maximum torque of 30Nm. The experimental results and the simulation data show that the maximum resultant errors are 6% for the PEM and 4% for the DEM respectively. In this paper, an assumed regression algorithm is used to learn the human motion intent (HMI) based on the pHRI collection. The HMI is defined as the angular position of the human limb joint. A closed-loop position control strategy is utilized to drive the robotic exoskeleton system to follow the human limb's movement. To verify the developed system, experiments are performed on healthy human subjects and experimental results show that this novel robotic exoskeleton can help human users walk, which can be extended and applied in the assistive wearable exoskeletons.

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Compared to the traditional pHRI measurement approaches, the proposed method arranged the sensors in the mechanical joint instead of the connection cuff. This kind of architecture has compact architecture and improves the wearing comfort, which can adapt to various operators and is convenient to be applied in the wearable exoskeleton. The performance of the DEM will be studied in the following work and human-exoskeleton coordination control strategies will be investigated in future work.
Compared to the traditional pHRI measurement approaches, the proposed method arranged the...
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