A digital twin framework for patrol robots with real-time path planning using optimised A* algorithm with ROS-Unity integration

The rapid advancement of digital twin (DT) technology has introduced new paradigms for improving safety, real-time control, and autonomy in robotic systems. However, challenges persist in achieving real-time synchronisation, robust environment perception, and reliable decision-making in dynamic environments. In this work, a real-time digital twin system for a patrol robot is proposed, combining Unity3D-based modelling and robot operating system ROS–TCP–Endpoint communication. To improve the path efficiency and responsiveness in uncertain environments, an optimised A* path planning algorithm with bidirectional control is presented using real-time obstacle detection. A five-layer architecture is presented to facilitate constant bidirectional mapping between the physical and virtual environments. Experimental validation demonstrates that the proposed DT framework achieves an average of 26% reduction in patrol path length and 9% shorter planning time over the traditional A* algorithm. The system achieves low synchronisation latency (<30 ms) at 25 m range and adapts hazard detection with a success rate of over 95%, proving the real-world viability of the approach for autonomous patrol scenarios.