TY - GEN
T1 - Developing a Digital Twin for Testing Multi-Agent Systems in Advanced Air Mobility
T2 - 42nd IEEE/AIAA Digital Avionics Systems Conference, DASC 2023
AU - Conrad, Christopher
AU - Delezenne, Quentin
AU - Mukherjee, Anurag
AU - Mhowwala, Ali Asgher
AU - Ahmed, Mohammad
AU - Zhao, Junjie
AU - Xu, Yan
AU - Tsourdos, Antonios
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Emerging unmanned aircraft system (UAS) and advanced air mobility (AAM) ecosystems rely on the development, certification and deployment of new and potentially intelligent technologies and algorithms. To promote a more efficient development life cycle, this work presents a digital twin architecture and environment to support the rapid prototyping and testing of multi-agent solutions for UAS and AAM applications. It leverages the capabilities of Microsoft AirSim and Cesium as plugins within the Unreal Engine 3D visualisation tool, and consolidates the digital environment with a flexible and scalable Python-based architecture. Moreover, the architecture supports hardware-in-the-loop (HIL) and mixed-reality features for enhanced testing capabilities. The system is comprehensively documented and demonstrated through a series of use cases, deployed within a custom digital environment, comprising both indoor and outdoor areas at Cranfield University and Airport. These include collaborative surveillance, UTM flight authorisation and UTM conformance monitoring experiments, that showcase the modularity, scalability and functionality of the proposed architecture. All 3D models and experimental observations are critically evaluated and shown to exhibit promising results. This thereby represents a critical step forward in the development of a robust digital twin for UAS and AAM applications.
AB - Emerging unmanned aircraft system (UAS) and advanced air mobility (AAM) ecosystems rely on the development, certification and deployment of new and potentially intelligent technologies and algorithms. To promote a more efficient development life cycle, this work presents a digital twin architecture and environment to support the rapid prototyping and testing of multi-agent solutions for UAS and AAM applications. It leverages the capabilities of Microsoft AirSim and Cesium as plugins within the Unreal Engine 3D visualisation tool, and consolidates the digital environment with a flexible and scalable Python-based architecture. Moreover, the architecture supports hardware-in-the-loop (HIL) and mixed-reality features for enhanced testing capabilities. The system is comprehensively documented and demonstrated through a series of use cases, deployed within a custom digital environment, comprising both indoor and outdoor areas at Cranfield University and Airport. These include collaborative surveillance, UTM flight authorisation and UTM conformance monitoring experiments, that showcase the modularity, scalability and functionality of the proposed architecture. All 3D models and experimental observations are critically evaluated and shown to exhibit promising results. This thereby represents a critical step forward in the development of a robust digital twin for UAS and AAM applications.
KW - Advanced air mobility
KW - AirSim
KW - UAS
KW - digital twin
KW - mixed-reality
KW - multi-agent
UR - https://www.scopus.com/pages/publications/85178665916
U2 - 10.1109/DASC58513.2023.10311333
DO - 10.1109/DASC58513.2023.10311333
M3 - 会议稿件
AN - SCOPUS:85178665916
T3 - AIAA/IEEE Digital Avionics Systems Conference - Proceedings
BT - DASC 2023 - Digital Avionics Systems Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 October 2023 through 5 October 2023
ER -