Special Issue: ICCAS 2024

International Journal of Control, Automation, and Systems 2025; 23(2): 489-497

https://doi.org/10.1007/s12555-024-0549-1

© The International Journal of Control, Automation, and Systems

Edge AI-driven Multi-camera System for Adaptive Robot Speed Control in Safety-critical Environments

Nak-Won Choi, Yeong-Bin Kim, and Bum Yong Park*

Kumoh National Institute of Technology

Abstract

This paper proposes a safety system for speed control of collaborative robots using multiple cameras and edge AI. Collaborative robots share the workspace with human workers, which requires a high level of safety for the workers. ISO/TS 15066 is a safety regulation for collaborative robots, and the proposed system establishes an additional safety system beyond the built-in safety regulations of collaborative robots. Using the edge AI-based YOLOv5n-seg, the system detects workers and estimates the distance through the instance segmentation coordinates used in object detection. The distance accuracy through the RGB-D camera shows an error rate of 3.55% at 3 meters. The adjusted base joint’s speed is 0.09 rad/s in normal mode. This is about 1/6 of the original maximum speed of 0.6 rad/s. When applying the speed reduction rate of the safety system, a robot operating at maximum speed in normal mode complies with the speed and distance regulations of ISO/TS 15066. Additionally, the robot’s response time from object detection is 0.806 seconds, confirming that worker safety can be effectively ensured.

Keywords Collaborative robot, edge AI, multiple camera, safety system.

Article

Special Issue: ICCAS 2024

International Journal of Control, Automation, and Systems 2025; 23(2): 489-497

Published online February 1, 2025 https://doi.org/10.1007/s12555-024-0549-1

Copyright © The International Journal of Control, Automation, and Systems.

Edge AI-driven Multi-camera System for Adaptive Robot Speed Control in Safety-critical Environments

Nak-Won Choi, Yeong-Bin Kim, and Bum Yong Park*

Kumoh National Institute of Technology

Abstract

This paper proposes a safety system for speed control of collaborative robots using multiple cameras and edge AI. Collaborative robots share the workspace with human workers, which requires a high level of safety for the workers. ISO/TS 15066 is a safety regulation for collaborative robots, and the proposed system establishes an additional safety system beyond the built-in safety regulations of collaborative robots. Using the edge AI-based YOLOv5n-seg, the system detects workers and estimates the distance through the instance segmentation coordinates used in object detection. The distance accuracy through the RGB-D camera shows an error rate of 3.55% at 3 meters. The adjusted base joint’s speed is 0.09 rad/s in normal mode. This is about 1/6 of the original maximum speed of 0.6 rad/s. When applying the speed reduction rate of the safety system, a robot operating at maximum speed in normal mode complies with the speed and distance regulations of ISO/TS 15066. Additionally, the robot’s response time from object detection is 0.806 seconds, confirming that worker safety can be effectively ensured.

Keywords: Collaborative robot, edge AI, multiple camera, safety system.

IJCAS
February 2025

Vol. 23, No. 2, pp. 359~682

Stats or Metrics

Share this article on

  • line

Related articles in IJCAS

IJCAS

eISSN 2005-4092
pISSN 1598-6446