Autonomous Docking in a Human-Robot Collaborative Environment of Automated Guided Vehicles
| Autor: | Chien-Wei Chiu, Ching-Hao Meng, Kai-Tai Song, Yu-Xuan Sun, Li-Ren Kang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
ComputingMethodologies_SIMULATIONANDMODELING business.industry Computer science Deep learning fungi technology industry and agriculture Navigation system ComputerApplications_COMPUTERSINOTHERSYSTEMS Automated guided vehicle Motion detection 02 engineering and technology 010501 environmental sciences 01 natural sciences Human–robot interaction 020901 industrial engineering & automation Docking (dog) Human–computer interaction DOCK Task analysis Artificial intelligence business 0105 earth and related environmental sciences |
| Zdroj: | 2020 International Automatic Control Conference (CACS). |
| DOI: | 10.1109/cacs50047.2020.9289713 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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