Unmanned Parallel Intelligent Search and Rescue System Based on Digital Twins
In response to the challenges of high-risk factors,inadequate global information understanding,and low decision-making efficien-cy in artificial rescue operations within unknown search and rescue scenarios,this study proposes integrating digital twins and robot clusters for efficient decision-making.Digital twins'visual integration and virtual inference capabilities are leveraged for unmanned execution of search and rescue tasks.A hierarchical multi-machine intelligent search and rescue digital twin framework is proposed along with a real-time model construction method based on SLAM.Each component is introduced in detail and theoretically analyzed.To address real-time mission requirements,the study designs online synchronization modules,collaborative target search and positioning modules,and parallel decision-making rescue path planning modules.These elements aim to overcome challenges such as asynchronous dynamics and inadequate accuracy in target search and positioning.Implemented in a Unity3D-based prototype system,the framework and modules are validated in simulated sce-narios,demonstrating reliability and efficiency.This research contributes valuable insights for enhancing artificial rescue operations.
urban search and rescuedigital twinparallel intelligenceunmanned systemscluster collaboration
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