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A Lightweight Ankle Exoskeleton Driven by Series Elastic Actuator

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Intelligent Robotics and Applications (ICIRA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14273))

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Abstract

The current research on exoskeleton torque control is relatively extensive, but the performance is suboptimal. Exoskeletons driven by series elastic actuator (SEA) can achieve high force control accuracy through simple position control. However, motor placement at the distal end increases the mass of the body terminal device, which not only increases the moment of inertia of the lower limb but also interferes with the normal movement of the patient, limiting their applicability in assisting the wearer. In this study, to prevent foot drop, we designed a lightweight, unilateral ankle exoskeleton that provides assistance for dorsiflexion via a single motor. By placing the motor and other heavier electronic components at the waist, the inertial load on the human leg is reduced achieving better assistance performance. Torque control assistance for the ankle joint is implemented using modified cascade PI control. When a person walks at a speed of 0.4 m/s, the desired maximum torque is set to 1.5 Nm, and the actual maximum torque is 1.5±0.187 Nm, which is close to the expected value. This demonstrates that the exoskeleton exhibits satisfactory force-tracking performance and can precisely assist individuals with foot drop in their daily walking activities.

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Acknowledgement

This work was supported in part by the National Natural Science Foundation of China [Grant U1913205, 52175272], in part by the Science, Technology, and Innovation Commission of Shenzhen Municipality [Grant: ZDSYS20200811143601004, JCYJ20220530114809021], and in part by the Stable Support Plan Program of Shenzhen Natural Science Fund under Grant 20200925174640002.

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Correspondence to Chenglong Fu .

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Du, H. et al. (2023). A Lightweight Ankle Exoskeleton Driven by Series Elastic Actuator. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14273. Springer, Singapore. https://doi.org/10.1007/978-981-99-6498-7_13

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  • DOI: https://doi.org/10.1007/978-981-99-6498-7_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6497-0

  • Online ISBN: 978-981-99-6498-7

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