Acta Mechanica Slovaca 2025, 29(1):14-20 | DOI: 10.21496/ams.2025.007

Use of Gaming Engines for Robotic Simulations and Computer Vision

Leo Brada1, *, Marek Málik1, Erik Prada1, Ľubica Miková1
Technical University of Kosice, Faculty of Mechanical Engineering, Department of Industrial Automation and Mechatronics, Park Komenského 8, 042 00 Košice

Gaming engines have evolved beyond their traditional role in entertainment, becoming powerful tools for robotic simulations and computer vision applications. Their ability to generate high-fidelity, real-time simulations makes them valuable for developing and testing robotic systems in virtual environments. The experiment demonstrated the use of the Unreal Engine, and its computer vision plugin called UnrealCV. A realistic factory environment was created in order to test the capability of the computer vision plugin. The article evaluates UnrealCV and its features along with their potential use in future work. Data from depth cameras are visualized in the form of 3D mesh and Yolo v5s AI image recognition software was tested.

Keywords: gaming engine, robotics, Unreal Engine, UnrealCV

Received: February 4, 2025; Accepted: March 2, 2025; Published: March 30, 2025  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Brada, L., Málik, M., Prada, E., & Miková, Ľ. (2025). Use of Gaming Engines for Robotic Simulations and Computer Vision. Acta Mechanica Slovaca29(1), 14-20. doi: 10.21496/ams.2025.007
Download citation

References

  1. . Zarco, L., Siegert, J., Schlegel, T. and Bauernhansl, T., 2021. Scope and delimitation of game engine simulations for ultra-flexible production environments. Procedia CIRP, 104, pp.792-797. Go to original source...
  2. . Whitney, D., Rosen, E., Ullman, D., Phillips, E. and Tellex, S., 2018, October. Ros reality: A virtual reality framework using consumer-grade hardware for ros-enabled robots. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1-9). IEEE. Go to original source...
  3. . Sita, E., Horváth, C.M., Thomessen, T., Korondi, P. and Pipe, A.G., 2017, December. ROS-Unity3D based system for monitoring of an industrial robotic process. In 2017 IEEE/SICE International Symposium on System Integration (SII) (pp. 1047-1052). IEEE. Go to original source...
  4. . Shamaine, C.X.E., Qiao, Y., Henry, J., McNevin, K. and Murray, N., 2020, September. RoSTAR: ROS-based telerobotic control via augmented reality. In 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP) (pp. 1-6). IEEE. Go to original source...
  5. . Martinez-Gonzalez, P., Oprea, S., Garcia-Garcia, A., Jover-Alvarez, A., Orts-Escolano, S. and Garcia-Rodriguez, J., 2020. Unrealrox: an extremely photorealistic virtual reality environment for robotics simulations and synthetic data generation. Virtual Reality, 24, pp.271-288. Go to original source...
  6. . Zaman, N., Tavakkoli, A. and Papachristos, C., 2020, April. 'Tele-robotics via an efficient immersive virtual reality architecture. In Proc. 3rd Int. Workshop Virtual, Augmented, Mixed Reality HRI.
  7. . Chaudhary, A., Mishra, R., Kalyan, B. and Chitre, M., 2021, September. Development of an underwater simulator using unity3d and robot operating system. In OCEANS 2021: San Diego-Porto (pp. 1-7). IEEE. Go to original source...
  8. . Meng, W., Hu, Y., Lin, J., Lin, F. and Teo, R., 2015, November. ROS+ unity: An efficient high-fidelity 3D multi-UAV navigation and control simulator in GPS-denied environments. In IECON 2015-41st Annual Conference of the IEEE Industrial Electronics Society (pp. 002562-002567). IEEE. Go to original source...
  9. . Shah, S., Dey, D., Lovett, C. and Kapoor, A., 2018. Airsim: High-fidelity visual and physical simulation for autonomous vehicles. In Field and Service Robotics: Results of the 11th International Conference (pp. 621-635). Springer International Publishing. Go to original source...
  10. . OpenCV team, OpenCV, from https://opencv.org/. Qiu, W. and Yuille, A., 2016. Unrealcv: Connecting computer vision to unreal engine. In Computer Vision-ECCV 2016Workshops: Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part III 14 (pp. 909-916). Springer International Publishing.12. Chaudhary, A., Tiwari, K. and Bera, A., 2023. HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System. arXiv preprint arXiv:2309.14508.13. Qiu, W., Zhong, F., Zhang, Y., Qiao, S., Xiao, Z., Kim, T. S., & Wang, Y. (2017, October). Unrealcv: Virtual worlds for computer vision. In Proceedings of the 25th ACM international conference on Multimedia (pp. 1221-1224).14. Jocher, Glenn, Ayush Chaurasia, Alex Stoken, Jirka Borovec, Yonghye Kwon, Kalen Michael, Jiacong Fang et al. "ultralytics/yolov5: v7. 0-yolov5 sota realtime instance segmentation." Zenodo (2022).

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.