Design and Development of an O-SEATER Simulation Platform for the BRIN Operational Area Using NVIDIA Isaac Sim

https://doi.org/10.5614/joki.2026.18.2.7

Authors

  • Rifki Rochiman Department of Computer Engineering, Universitas Pendidikan Indonesia, Bandung, 40154, Indonesia
  • Anugrah Adiwilaga Department of Computer Engineering, Universitas Pendidikan Indonesia, Bandung, 40154, Indonesia
  • Munawir Munawir Department of Computer Engineering, Universitas Pendidikan Indonesia, Bandung, 40154, Indonesia
  • Midriem Mirdanies Research Center for Smart Mechatronics, Badan Riset dan Inovasi Nasional, Bandung, 40135, Indonesia
  • Roni Permana Saputra Research Center for Smart Mechatronics, Badan Riset dan Inovasi Nasional, Bandung, 40135, Indonesia

Keywords:

digital twin, hardware-in-the-loop, NVIDIA Isaac Sim, o-seater, ROS 2

Abstract

Developing algorithms for mobile robot systems requires a simulation environment that models operational conditions. This research develops a simulation platform for the O-SEATER autonomous vehicle in the virtual environment of BRIN KST Samaun Samadikun using NVIDIA Isaac Sim. The virtual model was connected to the physical vehicle via a wireless network using the Robot Operating System 2 (ROS 2) for Hardware-in-the-Loop (HIL) and rosbag playback tests. The playback replicated the actual movements perfectly, with a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 0.0000 and an ideal Real-Time Factor (RTF) of 1.0010. HIL simulation ran 1.81 times slower (RTF = 0.5518), with a memory spike of 27.1 GiB, 214.63 ms network latency, and 15% packet loss. To compensate for this temporal deviation, we applied Dynamic Time Warping (DTW), resulting in high-precision HIL tracking (Linear X MAE = 0.0299 m/s; Angular Z MAE = 0.0224 rad/s). The high communication latency is an architectural limitation. Nevertheless, we achieved interactive communication and generated virtual sensor data (RGB and IMU). This platform remains a sufficiently valid algorithm-testing medium and the basis of the O-SEATER Digital Twin system.

References

J. Guo, M. Bilal, Y. Qiu, C. Qian, X. Xu, and K.-K. R. Choo, “Survey on digital twins for Internet of Vehicles: Fundamentals, challenges, and opportunities,” Digital Communications and Networks, vol. 10, no. 2, pp. 237–247, Apr. 2024. https://doi.org/10.1016/j.dcan.2022.05.023

X. Gu et al., “Digital twin technology for intelligent vehicles and transportation systems: A survey on applications, challenges and future directions,” IEEE Communications Surveys & Tutorials, vol. 28, pp. 3235–3271, 2026. https://doi.org/10.1109/COMST.2025.3581152

A. Fuller, Z. Fan, C. Day, and C. Barlow, “Digital twin: Enabling technologies, challenges and open research,” IEEE Access, vol. 8, pp. 108952–108971, 2020. https://doi.org/10.1109/ ACCESS.2020.2998358

National Research and Innovation Agency (BRIN), “BRIN develops the SEATER autonomous vehicle that can use an application,” BRIN News. [Online]. Available: https://brin.go.id/brin-kembangkan-kendaraan-otonom-seater-yang-bisa-pakai-aplikasi. Accessed: Jul. 27, 2026

S. Dharmaraj, “Indonesia: Sustainable, accessible and autonomous urban mobility,” OpenGov Asia, Nov. 11, 2024. [Online]. Available: https://opengovasia.com/indonesia-sustainable-accessible-and-autonomous-urban-mobility/. Accessed: Jul. 27, 2026

“Autonomous electric vehicles in restricted areas are being developed,” RRI.co.id, Nov. 2024. [Online]. Available: https://rri.co.id/iptek/1111984/about.html. Accessed: Jul. 27, 2026

S. M. Kargar, B. Yordanov, C. Harvey, and A. Asadipour, “Emerging trends in realistic robotic simulations: A comprehensive systematic literature review,” IEEE Access, vol. 12, pp. 191264–191287, 2024. https://doi.org/10.1109/ACCESS.2024.3404881

H. Alghodhaifi and S. Lakshmanan, “Autonomous vehicle evaluation: A comprehensive survey on modeling and simulation approaches,” IEEE Access, vol. 9, pp. 151531–151566, 2021. https://doi.org/10.1109/ACCESS.2021.3125620

S. D. Pendleton et al., “Perception, planning, control, and coordination for autonomous vehicles,” Machines, vol. 5, no. 1, Art. no. 6, 2017. doi: https://doi.org/10.3390/machines5010006

J. I. Da Silva Filho, C. L. M. Fernandes, R. S. d. Silveira, P. M. Gomes, S. L. d. C. Matos, L. d. E. Santo, V. C. Nunes, H. M. Côrtes, W. A. C. Lopes, M. C. Mario, D. V. Garcia, C. R. Torres, J. M. Abe, and G. Lambert-Torres, “Process of learning from demonstration with paraconsistent artificial neural cells for application in linear Cartesian robots,” Robotics, vol. 12, no. 3, Art. no. 69, 2023. https://doi.org/10.3390/robotics12030069

A. Al-Batati, A. Koubaa, K. Gabr, M. Abdelkader, and H. Aloqaily, “ROS 2 in a nutshell: A survey,” ACM Computing Surveys, 2025. https://doi.org/10.1145/3815113

A. Bonci, F. Gaudeni, M. C. Giannini, and S. Longhi, “Robot Operating System 2 (ROS2)-based frameworks for increasing robot autonomy: A survey,” Applied Sciences, vol. 13, no. 23, Art. no. 12796, 2023. https://doi.org/10.3390/app132312796

M. A. L. Sarker, M. O. F. Sarker, and D. S. Han, “A survey on digital twin-assisted intelligent vehicle localization,” ICT Express, vol. 11, no. 5, pp. 981–992, 2025. https://doi.org/10.1016/j.icte.2025.08.008

G. S. Lutz, S. Kubica, T. Peuschke-Bischof, and C. M. Travieso-González, “Digital driving twins for scaled ADAS algorithm development: A systematic review and design proposal for co-simulation architectures, indoor localization methods, and ground truth strategies,” Applied Sciences, vol. 16, no. 14, Art. no. 7261, 2026. https://doi.org/10.3390/app16147261

C. Campolo et al., “An edge-based digital twin framework for connected and autonomous vehicles: Design and evaluation,” IEEE Access, vol. 12, pp. 46290–46303, 2024. https://doi.org/10.1109/ACCESS.2024.3382001

Y. Hu, M. Wu, J. Kang, and R. Yu, “D-Tracking: Digital twin-enabled trajectory tracking system of autonomous vehicles,” IEEE Transactions on Vehicular Technology, vol. 73, no. 11, pp. 16457–16469, Nov. 2024. https://doi.org/10.1109/TVT.2024.3414410

S. Almeaibed, S. Al-Rubaye, A. Tsourdos, and N. P. Avdelidis, “Digital twin analysis to promote safety and security in autonomous vehicles,” IEEE Communications Standards Magazine, vol. 5, no. 1, pp. 40–46, Mar. 2021. https://doi.org/10.1109/MCOMSTD.011.2100004.

Ö. Kaya, L. Bacchiani, A. Melis, R. Presta, C.-T. Lam, G. Pau, and R. Girau, “Vehicle, driver, and road digital twins for connected mobility: A critical review and unified conceptual framework,” Future Internet, vol. 18, no. 6, Art. no. 277, 2026. https://doi.org/10.3390/fi18060277

X. Hu, S. Li, T. Huang, B. Tang, R. Huai, and L. Chen, “How simulation helps autonomous driving: A survey of Sim2Real, digital twins, and parallel intelligence,” IEEE Transactions on Intelligent Vehicles, vol. 9, no. 1, pp. 593–612, Jan. 2024. doi: https://doi.org/10.1109/TIV.2023.3312777

S. Cardozo and V. Hlavác, “CARLA hardware-in-the-loop simulation environment for autonomous driving,” SAE International Journal of Connected and Automated Vehicles, vol. 9, no. 2, pp. 289–309, 2026. https://doi.org/10.4271/12-09-02-0015

T.-M. Kim, S.-B. Lee, C.-Y. Lee, W.-P. Yu, and S.-H. Song, “A layered information model framework for standardizing digital twin simulation,” Journal of Institute of Control, Robotics and Systems, vol. 31, no. 12, pp. 1410–1417, 2025. https://doi.org/10.5302/J.ICROS.2025.25.0232

H. Sekkat, O. Moutik, B. El Kari, Y. Chaibi, T. Ait Tchakoucht, and A. El Hilali Alaoui, “Beyond simulation: Unlocking the frontiers of humanoid robot capability and intelligence with Pepper's open-source digital twin,” Heliyon, vol. 10, no. 14, Art. no. e34456, Jul. 2024. https://doi.org/10.1016/ j.heliyon.2024.e34456

D. J. Berndt and J. Clifford, "Using dynamic time warping to find patterns in time series," in Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining (KDD Workshop), 1994, pp. 359-370. [Online]. Available: https://dl.acm.org/doi/abs/10.5555/3000850.3000887

Z. Gao, T. Yu, T. Sun, and H. Zhao, “Data Filtering Method for Intelligent Vehicle Shared Autonomy Based on a Dynamic Time Warping Algorithm,” Sensors, vol. 22, no. 23, Art. no. 9436, Dec. 2022. https://doi.org/10.3390/s22239436

NVIDIA, "ROS 2 Publish Real Time Factor (RTF)," NVIDIA Isaac Sim Documentation. Available: https://docs.isaacsim.omniverse.nvidia.com. Accessed: Sep. 5, 2026

Published

2026-10-08

How to Cite

[1]
R. . Rochiman, A. . Adiwilaga, M. . Munawir, M. . Mirdanies, and R. P. Saputra, “Design and Development of an O-SEATER Simulation Platform for the BRIN Operational Area Using NVIDIA Isaac Sim”, JOKI, vol. 18, no. 2, pp. 259-278, Oct. 2026.

Issue

Vol. 18 No. 2 (2026): [FORTHCOMING] Jurnal Otomasi Kontrol dan Instrumentasi

Section

Articles
Copyright & Licensing

Copyright (c) 2026 Rifki Rochiman, Anugrah Adiwilaga, Munawir Munawir, Mirdanies Mirdanies, Midriem Mirdanies, Roni Permana Saputra

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