TY - GEN
T1 - AirTwinX
T2 - 22nd IEEE Consumer Communications and Networking Conference, CCNC 2025
AU - Dey, Annoy
AU - McManus, Maxwell
AU - Zhang, Zhaoxi
AU - Sun, Guanying
AU - Mastronarde, Nicholas
AU - Bentley, Elizabeth Serena
AU - Guan, Zhangyu
N1 - Publisher Copyright: © 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Ensuring the safety and reliability of emerging Advanced Aerial Mobility (AAM) systems requires wireless communication to provide real-time monitoring and control information to ground stations. This greatly depends on the quality of the wireless links during aerial transit. In this demonstration, we present AirTwinX, designed to emulate flight control of flying vehicles while generating high-fidelity, context-aware models for air-to-air (AA) and air-to-ground (AG) communication links. Using GPU-accelerated ray tracing, AirTwinX can predict the quality of wireless links with near real-time updates based on the environmental geometry observed during flight. This data is then used to guide autonomous control decision-making. Additionally, the vehicle control toolchain employed in this work is based on software-in-the-loop (SITL) emulation of a commercial flight controller, enabling seamless translation of control policies from simulation to real-world hardware.
AB - Ensuring the safety and reliability of emerging Advanced Aerial Mobility (AAM) systems requires wireless communication to provide real-time monitoring and control information to ground stations. This greatly depends on the quality of the wireless links during aerial transit. In this demonstration, we present AirTwinX, designed to emulate flight control of flying vehicles while generating high-fidelity, context-aware models for air-to-air (AA) and air-to-ground (AG) communication links. Using GPU-accelerated ray tracing, AirTwinX can predict the quality of wireless links with near real-time updates based on the environmental geometry observed during flight. This data is then used to guide autonomous control decision-making. Additionally, the vehicle control toolchain employed in this work is based on software-in-the-loop (SITL) emulation of a commercial flight controller, enabling seamless translation of control policies from simulation to real-world hardware.
KW - Advanced Air Mobility (AAM)
KW - NVIDIA GPU
KW - Ray Tracing
KW - Software-in-the-Loop (SITL)
UR - https://www.scopus.com/pages/publications/105005137143
U2 - 10.1109/CCNC54725.2025.10975938
DO - 10.1109/CCNC54725.2025.10975938
M3 - Conference contribution
T3 - Proceedings - IEEE Consumer Communications and Networking Conference, CCNC
BT - 2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 January 2025 through 13 January 2025
ER -