A Virtual Fencing Framework for Safe and Efficient Collaborative Robotics
For collaborative robotics practitioners, this provides a modular solution to enforce safety standards in real-time, but the results are incremental without concrete performance numbers.
The paper tackles real-time safety in human-robot collaboration by proposing a virtual fencing framework that models safety-performance tradeoffs as an optimization problem, solved via sequential quadratic programming. Experimental validation shows minimized operational pauses while maintaining safety.
Collaborative robots (cobots) increasingly operate alongside humans, demanding robust real-time safeguarding. Current safety standards (e.g., ISO 10218, ANSI/RIA 15.06, ISO/TS 15066) require risk assessments but offer limited guidance for real-time responses. We propose a virtual fencing approach that detects and predicts human motion, ensuring safe cobot operation. Safety and performance tradeoffs are modeled as an optimization problem and solved via sequential quadratic programming. Experimental validation shows that our method minimizes operational pauses while maintaining safety, providing a modular solution for human-robot collaboration.