The Journal of Korea Institute of Information, Electronics, and Communication Technology (한국정보전자통신기술학회논문지)

Korea Information Electronic Communication Technology (한국정보전자통신기술학회)
권호 표지
DOI QR코드

DOI QR Code

Design and Development of Modular Replaceable AI Server for Image Deep Learning in Social Robots on Edge Devices

엣지 디바이스인 소셜 로봇에서의 영상 딥러닝을 위한 모듈 교체형 인공지능 서버 설계 및 개발

  • Received : 2020.10.10
  • Accepted : 2020.11.02
  • Published : 2020.12.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we present the design of modular replaceable AI server for image deep learning that separates the server from the Edge Device so as to drive the AI block and the method of data transmission and reception. The modular replaceable AI server for image deep learning can reduce the dependency between social robots and edge devices where the robot's platform will be operated to improve drive stability. When a user requests a function from an AI server for interaction with a social robot, modular functions can be used to return only the results. Modular functions in AI servers can be easily maintained and changed by each module by the server manager. Compared to existing server systems, modular replaceable AI servers produce more efficient performance in terms of server maintenance and scale differences in the programs performed. Through this, more diverse image deep learning can be included in robot scenarios that allow human-robot interaction, and more efficient performance can be achieved when applied to AI servers for image deep learning in addition to robot platforms.

본 논문에서는 인공지능 블록을 구동할 수 있도록 Edge Device와 서버를 분리하는 영상 딥러닝용 모듈 교체형 인공지능 서버의 설계와 데이터 송수신 방법을 제시한다. 영상 딥러닝용 모듈 교체형 인공지능 서버를 통해 소셜 로봇과 로봇의 플랫폼이 구동될 Edge Device 간의 종속성을 줄여 구동 안정성을 향상할 수 있다. 사용자가 소셜 로봇과의 상호작용을 위해서 인공지능 서버에 기능을 요청하면 모듈화된 기능들을 이용해 결과만을 반환받을 수 있다. 인공지능 서버에서 모듈화되어있는 기능들은 서버 관리자에 의해 모듈별로 유지 보수 및 변경이 쉽게 가능하다. 기존 서버 시스템과 비교했을 때 모듈 교체형 인공지능 서버는 수행되는 프로그램의 규모 차이와 서버 유지 보수 면에서 더 효율적인 성능을 낸다. 이를 통해 사람-로봇 간의 상호작용이 가능한 로봇 시나리오에 더 다양한 영상 딥러닝을 포함 시킬 수 있으며, 로봇 플랫폼 외에 영상 딥러닝을 위한 인공지능 서버에 적용할 때 더 효율적인 성능을 낼 수 있다.

Keywords

References

  1. Dong-Hoon Lee, Seyun Jang, Hyekyung Cho, "MOCCA studio: a graphical tool for high-level programming of human-robot social interaction", HRI '19: Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, pp. 620-621, March, 2019.
  2. Khandelwal, Piyush, Shiqi Zhang, Jivko Sinapov, Matteo Leonetti, Jesse Thomason, Fangkai Yang, Ilaria Gori, "BWIBots: A Platform for Bridging the Gap between AI and Human-Robot Interaction Research.", The International Journal of Robotics Research 36, no. 5-7 : 635-59, June 2017 https://doi.org/10.1177/0278364916688949
  3. M. A. Salichs, "Maggie: A Robotic Platform for Human-Robot Social Interaction," 2006 IEEE Conference on Robotics, Automation and Mechatronics, Bangkok, pp. 1-7, 2006
  4. M. Hauck, R. Machhamer, L. Czenkusch, K. Gollmer and G. Dartmann, "Node and Block-Based Development Tools for Distributed Systems With AI Applications," in IEEE Access, vol. 7, pp. 143109-143119, 2019 https://doi.org/10.1109/access.2019.2940113
  5. Sukhpal Singh Gill, Shreshth Tuli, Minxian Xu, Inderpreet Singh, Karan Vijay Singh, Dominic Lindsay, Shikhar Tuli, Daria Smirnova, Manmeet Singh, Udit Jain, Haris Pervaiz, Bhanu Sehgal, Sukhwinder Singh Kaila, Sanjay Misra, Mohammad Sadegh Aslanpour, Harshit Mehta, Vlado Stankovski, Peter Garraghan, "Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing", Evolution, vision, trends and open challenges. CoRR abs/1911.01941, 2019
  6. A. H. Sodhro, S. Pirbhulal and V. H. C. de Albuquerque, "Artificial Intelligence-Driven Mechanism for Edge Computing-Based Industrial Applications," in IEEE Transactions on Industrial Informatics, vol. 15, no. 7, pp. 4235-4243, July 2019 https://doi.org/10.1109/tii.2019.2902878
  7. J. Redmon, S. Divvala, R. Girshick and A. Farhadi, "You Only Look Once: Unified, Real-Time Object Detection,", 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779-788, 2016
  8. CMU-Perceptual-Computing-La. OpenPose [Internet]. Available: https://github.com/CMU-Perceptual-ComputingLab/openpose
  9. face-recognition[Internet]. Available: https://github.com/ageitgey/face_recognition