Sensor-Based Virtual Fences for Industrial Robot Safety

Abstract

In industrial environments, safety has traditionally been ensured using physical barriers such as fences or enclosures to separate humans from robotic systems. While effective, these static solutions limit flexibility and make it difficult to adapt the layout to changing production needs. As factories become more dynamic and collaborative, there is a growing need for smarter, more adaptable safety systems. In this project, a virtual safety system for an industrial robot was developed using LiDAR sensors and real-time data processing. The system was designed to replace traditional physical barriers by creating three safety zones around the robot a safe zone, a warning zone and a restricted zone, depending on the distance of approaching objects. The sensors and control electronics were built and tested in real life, while the behavior and reactions of the robot were evaluated through simulation. The system continuously monitored the area at a height of 15 to 20 cm above the floor and successfully detected objects and classified them into the correct zones. The tests showed that the system detected all intrusions correctly in both warning and stop zones. The average response time was around 10 ms, which is fast enough for real-time feedback. However, the system experienced false intrusions in some cases, especially when using larger zones and more active components—up to 601 false triggers during 20 minutes recorded in one test. The results demonstrate that the system was able to trigger appropriate responses based on risk level, and show that virtual safety zones could be a viable and flexible alternative to traditional physical fences in industrial robot applications.