Autonomous Docking in a Human-Robot Collaborative Environment of Automated Guided Vehicles

Kai Tai Song, Chien Wei Chiu, Li Ren Kang, Yu Xuan Sun, Ching Hao Meng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we propose an autonomous docking and human-robot collaboration system for an automated guided vehicle (AGV). The AGV can not only navigate and dock autonomously, but also collaborate with the human by recognizing human in the environment. A human motion detection system is developed for the proposed human-robot collaboration design. A deep learning network is adopted to detect and recognize humans in the environment. By knowing of human motion, the AGV adjusts the automatic docking behavior in a collaborative manner. Practical experimental results demonstrate that human workers can co-exist with an AGV in an unstructured environment for autonomous docking tasks.

Original languageEnglish
Title of host publication2020 International Automatic Control Conference, CACS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728171982
DOIs
StatePublished - 4 Nov 2020
Event2020 International Automatic Control Conference, CACS 2020 - Hsinchu, Taiwan
Duration: 4 Nov 20207 Nov 2020

Publication series

Name2020 International Automatic Control Conference, CACS 2020

Conference

Conference2020 International Automatic Control Conference, CACS 2020
CountryTaiwan
CityHsinchu
Period4/11/207/11/20

Keywords

  • Autonomous Docking
  • Human recognition
  • Human-Robot Collaboration
  • Navigation System

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