Digital Twins have been used not only in the Design phase for enabling effective communication among stakeholders for System-Level Design iterations but also throughout the Engineering Life Cycle. For constructing a Digital Twin of an environment, Multi-Agent Systems composed of multiple interacting manned and/or unmanned systems conduct Collaborative Simultaneous Localization And Mapping (CSLAM) and solve a Pose-Graph Optimization (PGO) Problem to estimate their trajectories based on relative inter-agent and intra-agent measurements. The project aims at developing the technological foundations on Collaborative Multi-Agent Systems Pose-Graph Optimization (CMASPGO) For Digital Twins for enhancing the automation level and improving the system performance even in some GPS-denied environments. In this project, computational algorithms and software for Pose-Graph Optimization Problem will be developed and validated by adopting the Model-Based Systems Engineering (MBSE) for complex environments arised in Smart City applications. The developed technologies can enable industrial customers on deploying many more manned and/or unmanned systems for conducting sophisticated Collaborative Simultaneous Localization And Mapping for building Digital Twins in Smart City applications.
