Journal of Internet of Things and Convergence (사물인터넷융복합논문지)

The Korea Internet of Things Society (한국사물인터넷학회)
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Legged Robot Trajectory Generation using Evolved Fuzzy Machine for IoT Environments

IoT 환경을 위한 진화된 퍼지머신을 이용한 로봇의 궤적생성

  • Kim, Dong Won (Dept. of Digital Electronics, Inha Technical College)
  • 김동원 (인하공업전문대학 디지털전자과)
  • Received : 2020.08.24
  • Accepted : 2020.09.09
  • Published : 2020.09.30
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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.

일상에서 이용하는 모든 물건들이 네트워크 접속 기능을 갖추고, 이들이 긴밀하게 연동하면서 생활 및 업무의 편의성을 높이는 IoT(사물인터넷) 시대가 활짝 열렸다. 로봇도 IoT 환경에 맞춰 발전해야 하는 상황이다. 논문에서는 IoT 환경을 위한 다리가 있는 로봇 궤적을 생성하기 위해 새로운 형태의 EFM (진화 퍼지 머신)을 사용하는 방법에 대하여 다룬다. 퍼지 시스템은 비선형 시스템을 묘사하는 데 널리 사용되고 있다. 퍼지 시스템에서 퍼지 모델의 전반부 및 후반부 구조를 결정하는 것은 매우 중요한 문제이다. EFM은 다리가 달린 로봇을 위해 퍼지 시스템의 전반부 및 후반부 구조를 진화시켜 효율적으로 구조를 개선한다. 퍼지 시스템에서 각 구조의 로봇 궤적 매개 변수를 생성하고 EFM에 의해 자동으로 조정된다. 제안된 접근 방식은 다리가 있는 로봇에 적용하여 성능을 살펴본다.

Keywords

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