Journal of Drive and Control (드라이브 ㆍ 컨트롤)

The Korean Society for Fluid Power and Construction Equipment (유공압건설기계학회)
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The Study of Barista Robots Utilizing Collaborative Robotics and AI Technology

협동로봇과 AI 기술을 활용한 바리스타 로봇 연구

  • Do Hyeong Kwon (Department of Mechanical Engineering, Inha University) ;
  • Tae Myeong Ha (Department of Mechanical Engineering, Inha University) ;
  • Jae Seong Lee (Department of Mechanical Engineering, Inha University) ;
  • Yun Sang Jeong (Department of Mechanical Engineering, Inha University) ;
  • Yeong Geon Kim (Department of Mechanical Engineering, Inha University) ;
  • Hyeon Gak Kim (Department of Mechanical Engineering, Inha University) ;
  • Seung Jun Song (Department of Mechanical Engineering, Inha University) ;
  • Dae Gil O (Department of Mechanical Engineering, Inha University) ;
  • Geonu Lee (Department of Mechanical Engineering, Inha University) ;
  • Jae Won Jeong (Department of Mechanical Engineering, Inha University) ;
  • Seungwoon Park (Department of Mechanical Engineering, Inha University) ;
  • Chul-Hee Lee (Department of Mechanical Engineering, Inha University)
  • Received : 2024.08.07
  • Accepted : 2024.08.29
  • Published : 2024.09.01
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Abstract

Collaborative robots, designed for direct interaction with humans have limited adaptability to environmental changes. This study addresses this limitation by implementing a barista robot system using AI technology. To overcome limitations of traditional collaborative robots, a model that applies a real-time object detection algorithm to a 6-degree-of-freedom robot arm to recognize and control the position of random cups is proposed. A coffee ordering application is developed, allowing users to place orders through the app, which the robot arm then automatically prepares. The system is connected to ROS via TCP/IP socket communication, performing various tasks through state transitions and gripper control. Experimental results confirmed that the barista robot could autonomously handle processes of ordering, preparing, and serving coffee.

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Acknowledgement

이 논문은 2024년도 정부(산업통상자원부)의 재원으로 한국산업기술진흥원의 지원을 받아 수행된 연구임 (P0020612, 2024년 산업혁신인재성장지원사업)

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