Intuitive Gait Pattern Generation for an Exoskeleton Robot

  • S. H. Hwang
  • S. C. Lee
  • D. B. Shin
  • I. H. Baek
  • M. J. Kim
  • D. I. Sun
  • B. S. Kim
  • S. W. Hwang
  • C. S. HanEmail author
Regular Paper


Exoskeleton robots are being studied and developed in various forms according to user. Among them, the most concentrated area is the lower limb exoskeleton robot for “walking,” which is the basic exercise of paralyzed patients. In this study, we utilize the gait cycle, speed, and stride, which are important dependent factors of gait, and not the control technique that uses the predefined gait pattern using the average value of the gait data of the general person used by the existing rehabilitation exoskeleton robot. By creating an end-point reference using a walking element and inverse kinematics, and by using a dynamic movement primitive technique to learn the gait data of the general public, generating the gait patterns of various walking environments without storing them in advance is possible. In this paper, we applied this method to the exoskeleton robot and show robot to generate various strides gait pattern by experiments.


Lower extremity exoskeleton robot Gait pattern generation Rehabilitation robot Dynamic movement primitives 

List of Symbols

\(p_{h} ,p_{k}\)

Position of Pelvis and Knee


Robot pelvis to knee link length


Robot knee to foot link length

\(\theta_{h} ,\theta_{k}\)

Joint angle of hip and knee

\(x_{h} ,y_{h} ,x_{k} ,y_{k}\)

Joint position of hip and knee



This paper is the result of the basic research project (NRF-2018R1D1A1B07050021) that was supported by the Korea Research Foundation.


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Copyright information

© Korean Society for Precision Engineering 2019

Authors and Affiliations

  1. 1.Department of Mechatronics EngineeringHanyang UniversityAnsan-siRepublic of Korea
  2. 2.Department of Interdisciplinary Engineering SystemHanyang UniversityAnsan-siRepublic of Korea
  3. 3.Industry University Cooperation FoundationHanyang University ERICAAnsan-siRepublic of Korea
  4. 4.Korea Institute of Manufacturing InnovationAnsan-siRepublic of Korea
  5. 5.Department of Robot EngineeringHanyang UniversityAnsan-siRepublic of Korea

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