Related Experiment Video
Updated: Jul 29, 2026
10:32
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
Published on: August 15, 2016
15.5K
Novel Robotic Arm Working-Area AI Protection System
Jeng-Dao Lee1, En-Shuo Jheng1, Chia-Chen Kuo1
1Department of Automation Engineering, National Formosa University, Yunlin County 632, Taiwan.
Sensors (Basel, Switzerland)
|March 11, 2023
Summary
This study introduces a new algorithm using YOLOv4 tiny-object detection to identify workers in dangerous zones around robotic arms. The system achieves 97% recognition accuracy and stops the arm within 50 ms, enhancing factory safety.
Area of Science:
- Robotics and Automation
- Artificial Intelligence
- Industrial Safety
Background:
- Automated factories involve complex machinery like robotic arms and CNC operations, posing significant risks to human workers.
- Traditional safety measures may be insufficient for advanced human-robot collaboration environments.
- Ensuring worker safety is paramount in modern manufacturing settings.
Purpose of the Study:
- To develop and validate a novel warning-range algorithm for detecting human presence in hazardous work zones.
- To enhance the accuracy of object detection for improved safety in automated industrial environments.
- To implement a real-time safety system for human-robot collaboration.
Main Methods:
- Implementation of YOLOv4 tiny-object detection algorithms for precise identification of individuals.
- Development of an efficient warning-range algorithm to determine proximity to dangerous machinery.
- Integration with a stack light for visual alerts and an M-JPEG streaming server for browser-based image display.
Main Results:
- The system demonstrated a recognition accuracy of 97% in experimental setups on a robotic arm workstation.
- The safety system successfully stopped the robotic arm within approximately 50 milliseconds upon detecting a person in the danger zone.
- Real-time monitoring and alerts were effectively provided through the stack light and M-JPEG streaming.
Conclusions:
- The proposed warning-range algorithm effectively enhances worker safety in automated factories.
- The integration of YOLOv4 tiny-object detection significantly improves the accuracy of human presence detection.
- This system offers a reliable solution for real-time safety monitoring in human-robot collaboration scenarios.
More Related Videos
Related Concept Videos
01:22Mechanical Systems
Mechanical systems are analogous to to electrical networks where springs and masses play similar roles to inductors and capacitors, respectively. A viscous damper in mechanical systems functions similarly to a resistor in electrical networks, dissipating energy. The forces acting on a mass in such systems include an applied force in the direction of motion, counteracted by forces from the spring, a viscous damper, and the mass's acceleration. This interplay of forces is mathematically described...
01:23Radial System Protection
Radial systems employ time-delay overcurrent relays to reduce load interruptions. When a fault occurs, the nearest breaker opens first, while upstream breakers remain closed due to longer delay settings. This approach ensures minimal disruption to the rest of the system.
In a radial system with a fault downstream of the third breaker, ideally, only the third breaker will open, isolating the fault and interrupting the load connected beyond it. The second breaker has a longer delay setting,...
In a radial system with a fault downstream of the third breaker, ideally, only the third breaker will open, isolating the fault and interrupting the load connected beyond it. The second breaker has a longer delay setting,...