UNetyEmuROS: A Unity-Based Multi-Vehicle Simulator with Physically-Grounded Dynamics and ROS2 Sensor Integration
Resumo
We present UNetyEmuROS, a Unity-based multi-vehicle simulator that extends our previous work UNetyEmu with two key contributions: (i) a physically-grounded dynamics engine featuring per-motor forces, cascaded PID attitude control, and actuator disk energy modeling, where picking up a package physically alters thrust demand, inertia, and battery drain as emergent behavior; and (ii) a modular ROS2 sensor bridge publishing 360-LiDAR, RGB and depth camera, IMU, and GPS as standard sensor msgs topics, each independently attachable to any vehicle. We validate both contributions in an urban scenario with heterogeneous drones and ground vehicles operating concurrently on package delivery tasks, object detection, and teleoperation through ROS.Referências
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Macenski, S., Foote, T., Gerkey, B., Lalancette, C., and Woodall, W. (2022). Robot operating system 2: Design, architecture, and uses in the wild. Science Robotics, 7(66):eabm6074.
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Pounds, P., Mahony, R., and Corke, P. (2010). Modelling and control of a large quadrotor robot. Control Engineering Practice, 18(7):691–699. Special Issue on Aerial Robotics.
Rodriguez, M., de Castro, A., Santana, I., Fontes, R., Rodriguez, F., and Rothenberg, C. (2025a). Unetyemu: Unity-based simulator for aerial and non-aerial vehicles with integrated network emulation. In Companion Proceedings of the 43rd Brazilian Symposium on Computer Networks and Distributed Systems, pages 100–111, Porto Alegre, RS, Brasil. SBC.
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Shah, S., Dey, D., Lovett, C., and Kapoor, A. (2018). Airsim: High-fidelity visual and physical simulation for autonomous vehicles. In Hutter, M. and Siegwart, R., editors, Field and Service Robotics, pages 621–635, Cham. Springer International Publishing.
Song, Y., Naji, S., Kaufmann, E., Loquercio, A., and Scaramuzza, D. (2021). Flightmare: A flexible quadrotor simulator. In Kober, J., Ramos, F., and Tomlin, C., editors, Proceedings of the 2020 Conference on Robot Learning, volume 155 of Proceedings of Machine Learning Research, pages 1147–1157. PMLR.
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Chovancová, A., Fico, T., Ľuboš Chovanec, and Hubinsk, P. (2014). Mathematical modelling and parameter identification of quadrotor (a survey). Procedia Engineering, 96:172–181. Modelling of Mechanical and Mechatronic Systems.
Dorling, K., Heinrichs, J., Messier, G. G., and Magierowski, S. (2017). Vehicle routing problems for drone delivery. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(1):70–85.
Faessler, M., Falanga, D., and Scaramuzza, D. (2017). Thrust mixing, saturation, and body-rate control for accurate aggressive quadrotor flight. IEEE Robotics and Automation Letters, 2(2):476–482.
Jocher, G., Qiu, J., and Chaurasia, A. (2023). Ultralytics YOLO. [link]. Accessed: 2026-03-26.
Juliani, A., Berges, V.-P., Teng, E., Cohen, A., Harper, J., Elion, C., Goy, C., Gao, Y., Henry, H., Mattar, M., and Lange, D. (2020). Unity: A general platform for intelligent agents.
Kishore, K., Dalai, S., Jangir, Y., Singh, S., Rohan, M., Shashank, D., Katta, S. S. S., and Saha, S. K. (2022). 3d pure pursuit guidance of drones for autonomous precision landing. In 2022 13th Asian Control Conference (ASCC), pages 2218–2222.
Koenig, N. and Howard, A. (2004). Design and use paradigms for gazebo, an open-source multi-robot simulator. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), volume 3, pages 2149–2154 vol.3.
Macenski, S., Foote, T., Gerkey, B., Lalancette, C., and Woodall, W. (2022). Robot operating system 2: Design, architecture, and uses in the wild. Science Robotics, 7(66):eabm6074.
Mahony, R., Kumar, V., and Corke, P. (2012). Multirotor aerial vehicles: Modeling, estimation, and control of quadrotor. IEEE Robotics and Automation Magazine, 19(3):20–32.
Makahleh, H. Y., Ferranti, E. J. S., and Dissanayake, D. (2024). Assessing the role of autonomous vehicles in urban areas: A systematic review of literature. Future Transportation, 4(2):321–348.
Mueller, M. W. and D’Andrea, R. (2014). Stability and control of a quadrocopter despite the complete loss of one, two, or three propellers. In 2014 IEEE International Conference on Robotics and Automation (ICRA), pages 45–52.
Munasinghe, I., Perera, A., and Deo, R. C. (2024). A comprehensive review of uav-ugv collaboration: Advancements and challenges. Journal of Sensor and Actuator Networks, 13(6).
Pounds, P., Mahony, R., and Corke, P. (2010). Modelling and control of a large quadrotor robot. Control Engineering Practice, 18(7):691–699. Special Issue on Aerial Robotics.
Rodriguez, M., de Castro, A., Santana, I., Fontes, R., Rodriguez, F., and Rothenberg, C. (2025a). Unetyemu: Unity-based simulator for aerial and non-aerial vehicles with integrated network emulation. In Companion Proceedings of the 43rd Brazilian Symposium on Computer Networks and Distributed Systems, pages 100–111, Porto Alegre, RS, Brasil. SBC.
Rodriguez, M., de Castro, A. G., Fontes, R., Rodriguez, F., and Rothenberg, C. (2025b). An integrated framework for network emulation and multi-vehicle algorithm testing. In Proceedings of the ACM SIGCOMM 2025 Posters and Demos, ACM SIGCOMM Posters and Demos ’25, page 167–169, New York, NY, USA. Association for Computing Machinery.
Shah, S., Dey, D., Lovett, C., and Kapoor, A. (2018). Airsim: High-fidelity visual and physical simulation for autonomous vehicles. In Hutter, M. and Siegwart, R., editors, Field and Service Robotics, pages 621–635, Cham. Springer International Publishing.
Song, Y., Naji, S., Kaufmann, E., Loquercio, A., and Scaramuzza, D. (2021). Flightmare: A flexible quadrotor simulator. In Kober, J., Ramos, F., and Tomlin, C., editors, Proceedings of the 2020 Conference on Robot Learning, volume 155 of Proceedings of Machine Learning Research, pages 1147–1157. PMLR.
Sow, A., Rodriguez, M., de Oliveira, F., Wzorek, M., de Leng, D., Tiger, M., Heintz, F., and Rothenberg, C. (2026). Multi uavs preflight planning in a shared and dynamic airspace. In Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026). Accepted for publication.
Unity Technologies (2026a). ROS-TCP-Connector. [link]. Accessed: 2026-03-26.
Unity Technologies (2026b). ROS-TCP-Endpoint. [link]. Accessed: 2026-03-26.
Publicado
25/05/2026
Como Citar
CAPOVILLA, Felipe Pavanello; CESEN, Mauricio Rodriguez; ROTHENBERG, Christian Esteve.
UNetyEmuROS: A Unity-Based Multi-Vehicle Simulator with Physically-Grounded Dynamics and ROS2 Sensor Integration. In: SALÃO DE FERRAMENTAS - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 44. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 177-186.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2026.23254.
