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Virtual model control of lower extremity exoskeleton for load carriage inspired by human behavior

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Abstract

The most significant feature of the exoskeleton system, which distinguishes it from other robotic systems, is the symbiotic relationship between the exoskeleton and the wearer. For perfect symbiotic relationship, the exoskeleton should be able to exactly detect the wearer’s intention to move. Existing methods by which lower extremity exoskeletons can detect human intentions are highly dependent on additional sensor systems or accurate dynamic models. In this paper, we propose a novel method for detecting human intention inspired by human behavior, and a control method that utilizes it. We define human intention as the tendency of humans to maintain a statically stable posture and minimize joint torques when supporting payloads. The control method reduces the computational requirements and simplifies the exoskeleton sensor system compared to existing methods. The experimentally measured ground reaction force was used to indirectly estimate the effects of our method on the wearer. The results suggest that the proposed method reduces the load acting on the wearer during locomotion under loaded conditions, and results in a portion of his body weight being supported by the exoskeleton when he is in an uncomfortable position.

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Acknowledgments

This work was partially supported by the Industrial Strategic technology development program (No. 10035431, Development of Wearable Robot for Industrial Labor Support) funded by the Ministry of Trade, Industry and Energy (MI, Korea) and partially supported by the Ministry of Knowledge Economy (MKE, Korea), under the Advanced Robot Manipulation Research Center support program supervised by National IT Industry Promotion Agency (NIPA), NIPA-2013-H1502-13-1001.

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Authors and Affiliations

  1. Department of Intelligent Robot Engineering, University of Science and Technology (UST), Ansan, Gyeonggi-do, Republic of Korea

    Jong-won Lee

  2. Advanced Robotics Laboratory, Department of Mechatronics Engineering, Hanyang University, Ansan, Gyeonggi-do, Republic of Korea

    Hyogon Kim

  3. Robotics R&BD Group, Korea Institute of Industrial Technology (KITECH), Ansan, Gyeonggi-do, Republic of Korea

    Jaeho Jang & Sangdeok Park

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  1. Jong-won Lee
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  4. Sangdeok Park
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Correspondence to Sangdeok Park.

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Lee, Jw., Kim, H., Jang, J. et al. Virtual model control of lower extremity exoskeleton for load carriage inspired by human behavior. Auton Robot 38, 211–223 (2015). https://doi.org/10.1007/s10514-014-9404-1

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