BROWSE
Detail
Conference Paper
Safety Monitoring for Human Robot Collaborative Workspaces
Cited 3 time in 
Share 
Share
- Authors
- Sangseung Kang, Minjong Kim, Kyekyung Kim
- Issue Date
- 2019-10
- Citation
- International Conference on Control, Automation and Systems (ICCAS) 2019, pp.1192-1194
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- The demand for robots for the automation of the manufacturing process is steadily increasing. This is also true in the cell manufacturing process in which the entire manufacturing process is worker-centered. When automating such manufacturing processes with robots, technical methods for ensuring the safety of the workers must be secured. This paper proposes a safety monitoring system to provide the safety of the workers by estimating the distance between a worker and a robot in a collaborative manufacturing environment. The proposed system detects the position of a worker and a robot from the depth images using a deep neural network model and estimates the distance to recognize any dangerous situations that a worker may face. It makes it possible for workers to safely work in the collaborative workspaces by avoiding vulnerable situations with robot control.
- KSP Keywords
- Cell manufacturing, Collaborative manufacturing, Deep neural network(DNN), Depth image, Manufacturing environment, Manufacturing processes, Monitoring system, Neural network model, Robot Control, Safety Monitoring, neural network(NN)