반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
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딥러닝 기반 자율주행 계단 등반 물품운송 로봇 개발

Development of Stair Climbing Robot for Delivery Based on Deep Learning

  • 문기일 (한국기술교육대학교 메카트로닉스공학부) ;
  • 이승현 (한국기술교육대학교 메카트로닉스공학부) ;
  • 추정필 (한국기술교육대학교 메카트로닉스공학부) ;
  • 오연우 (한국기술교육대학교 메카트로닉스공학부) ;
  • 이상순 (한국기술교육대학교 메카트로닉스공학부)
  • Mun, Gi-Il (School of Mechatronics Engineering, Korea University of Technology and Education) ;
  • Lee, Seung-Hyeon (School of Mechatronics Engineering, Korea University of Technology and Education) ;
  • Choo, Jeong-Pil (School of Mechatronics Engineering, Korea University of Technology and Education) ;
  • Oh, Yeon-U (School of Mechatronics Engineering, Korea University of Technology and Education) ;
  • Lee, Sang-Soon (School of Mechatronics Engineering, Korea University of Technology and Education)
  • 투고 : 2022.12.02
  • 심사 : 2022.12.16
  • 발행 : 2022.12.31
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초록

This paper deals with the development of a deep-learning-based robot that recognizes various types of stairs and performs a mission to go up to the target floor. The overall motion sequence of the robot is performed based on the ROS robot operating system, and it is possible to detect the shape of the stairs required to implement the motion sequence through rapid object recognition through YOLOv4 and Cuda acceleration calculations. Using the ROS operating system installed in Jetson Nano, a system was built to support communication between Arduino DUE and OpenCM 9.04 with heterogeneous hardware and to control the movement of the robot by aligning the received sensors and data. In addition, the web server for robot control was manufactured as ROS web server, and flow chart and basic ROS communication were designed to enable control through computer and smartphone through message passing.

키워드

과제정보

본 연구는 한국기술교육대학교의 지원에 의해 이루어졌음.

참고문헌

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