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Legged Robot Trajectory Generation using Evolved Fuzzy Machine for IoT Environments

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2020, 6(3), pp.59-65
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : August 24, 2020
  • Accepted : September 9, 2020
  • Published : September 30, 2020

Dong W. Kim 1

1인하공업전문대학

Candidate

ABSTRACT

The Internet of Things (IoT) era, in which all items used in daily life are equipped with a network connection function, and they are closely linked to increase the convenience of life and work, has opened wide. Robots also need to develop according to the IoT environment. A use of new type of evolved fuzzy machine (EFM) for generating legged robot trajectory in IoT enviornmentms is discussed in this paper. Fuzzy system has been widely used for describing nonlinear systems. In fuzzy system, determination of antecedent and consequent structures of fuzzy model has been one of the most important problems. EFM is described which carries out evolving antecedent and consequent structure of fuzzy system for legged robot. To generate the robot trajectory, parameters of each structure in the fuzzy system are tuned automatically by the EFM. The results demonstrate the performance of the proposed approach for the legged robot.

Citation status

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