Skip to main content

Human Rescue Based on Autonomous Robot KUKA YouBot with ROS and Object Detection

  • Conference paper
  • First Online:
Intelligent Systems and Applications (IntelliSys 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

Included in the following conference series:

Abstract

The rescue processes that must be carried out in environments that present contamination levels are limited by the exposure time to which rescuers can be submitted, due to this the use of robotic platforms has been taken as a feasible option since it allows to increase the precision when carrying out the operations and to reduce the time in the decision making. In this paper is presented a system which uses the Kuka Youbot mobile platform to perform navigation processes, exploration and detection of people, in order to generate a map which contains the locations of individuals detected. The processes are executed through the combination of Robot Operating System and Open Source Computer Vision Library, in addition the complete system is simulated within the environment of Gazebo. The detection of individuals is done by implementing the Single Shot Detector algorithm and using a trained neural network. The simulation of the system made it possible to detect people inside a building in spite of occlusions in the captured images and it was possible to save the coordinates of their locations to later generate marks inside a 2D generated map.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Doroodgar, B., Liu, Y., Nejat, G.: A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims. IEEE Trans. Cybern. 44(12), 2719–2732 (2014)

    Article  Google Scholar 

  2. Geng, N., Gong, D.W., Zhang, Y.: PSO-based robot path planning for multisurvivor rescue in limited survival time. Math. Probl. Eng. 2014, 1–10 (2014)

    Google Scholar 

  3. Phuengsuk, R., Suthakorn, J.: A study on risk assessment for improving reliability of rescue robots. In: 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), Qingdao, China, pp. 667–672 (2016)

    Google Scholar 

  4. Xia, F., Tyoan, L., Yang, Z., Uzoije, I., Zhang, G., Vela, P.A.: Human-aware mobile robot exploration and motion planner. In: SoutheastCon 2015, Fort Lauderdale, FL, USA, pp. 1–4 (2015)

    Google Scholar 

  5. Hsu, S.-C., Wang, Y.-W., Huang, C.-L.: Human Object identification for human-robot interaction by using fast R-CNN. In: 2018 Second IEEE International Conference on Robotic Computing (IRC), Laguna Hills, CA, pp. 201–204 (2018)

    Google Scholar 

  6. Xin, C., Qiao, D., Hongjie, S., Chunhe, L., Haikuan, Z.: Design and implementation of debris search and rescue robot system based on internet of things. In: 2018 International Conference on Smart Grid and Electrical Automation (ICSGEA), Changsha, pp. 303–307 (2018)

    Google Scholar 

  7. Shin, S., Yoon, D., Song, H., Kim, B., Han, J.: Communication system of a segmented rescue robot utilizing socket programming and ROS. In: 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Jeju, pp. 565–569 (2017)

    Google Scholar 

  8. Liu, W., et al.: SSD: single shot MultiBox detector. In: vol. 9905, pp. 21–37, ArXiv151202325 Cs (2016)

    Google Scholar 

  9. Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137–1149 (2017)

    Article  Google Scholar 

  10. Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, pp. 779–788 (2016)

    Google Scholar 

  11. Quigley, M., et al.: ROS: an open-source Robot Operating System, p. 6 (2009)

    Google Scholar 

  12. Denker, A., Iseri, M.C.: Design and implementation of a semi-autonomous mobile search and rescue robot: SALVOR. In: 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, pp. 1–6 (2017)

    Google Scholar 

  13. Guowei, Z., et al.: Development of robotic spreader for earthquake rescue. In: 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (2014), Hokkaido, Japan, pp. 1–5 (2014)

    Google Scholar 

  14. Kahn, G., Villaflor, A., Ding, B., Abbeel, P., Levine, S.: Self-supervised deep reinforcement learning with generalized computation graphs for robot navigation. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, pp. 1–8 (2018)

    Google Scholar 

  15. Bischoff, R.: KUKA youBot – a milestone for education and research in mobile manipulation, p. 25

    Google Scholar 

  16. Takaya, K., Asai, T., Kroumov, V., Smarandache, F.: Simulation environment for mobile robots testing using ROS and Gazebo. In: 2016 20th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, pp. 96–101 (2016)

    Google Scholar 

  17. Htike, K.K., Khalifa, O.O., Mohd Ramli, H.A., Abushariah, M.A.M.: Human activity recognition for video surveillance using sequences of postures. In: The Third International Conference on e-Technologies and Networks for Development (ICeND2014), Beirut, Lebanon, pp. 79–82 (2014)

    Google Scholar 

  18. Fuentes-Pacheco, J., Ruiz-Ascencio, J., Rendón-Mancha, J.M.: Visual simultaneous localization and mapping: a survey. Artif. Intell. Rev. 43(1), 55–81 (2015)

    Article  Google Scholar 

  19. Perez, A., Karaman, S., Shkolnik, A., Frazzoli, E., Teller, S., Walter, M.R.: Asymptotically-optimal path planning for manipulation using incremental sampling-based algorithms. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, pp. 4307–4313 (2011)

    Google Scholar 

  20. Galli, M., Barber, R., Garrido, S., Moreno, L.: Path planning using Matlab-ROS integration applied to mobile robots. In: 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Coimbra, Portugal, pp. 98–103 (2017)

    Google Scholar 

  21. Angelov, P.P., Gu, X.: Toward anthropomorphic machine learning. Computer 51(9), 18–27 (2018)

    Article  Google Scholar 

  22. Liu, Y., et al: The design of a fully autonomous robot system for urban search and rescue. In: 2016 IEEE International Conference on Information and Automation (ICIA), Ningbo, China, pp. 1206–1211 (2016)

    Google Scholar 

  23. Chen, X., Zhang, H., Lu, H., Xiao, J., Qiu, Q., Li, Y.: Robust SLAM system based on monocular vision and LiDAR for robotic urban search and rescue. In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), Shanghai, China, pp. 41–47 (2017)

    Google Scholar 

  24. Shang, Y.: Resilient multiscale coordination control against adversarial nodes. Energies 11(7), 1844 (2018)

    Article  Google Scholar 

Download references

Acknowledgment

The authors thank the Technical University of Ambato and the “Dirección de Investigación y Desarrollo” (DIDE) for their support in carrying out this research, in the execution of the project “Plataforma Móvil Omnidireccional KUKA dotada de Inteligencia Artificial utilizando estrategias de Machine Learnig para Navegación Segura en Espacios no Controlados”, project code: PFISEI27.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Carlos Gordón , Patricio Encalada , Henry Lema , Diego León or Dennis Chicaiza .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gordón, C., Encalada, P., Lema, H., León, D., Chicaiza, D. (2020). Human Rescue Based on Autonomous Robot KUKA YouBot with ROS and Object Detection. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_58

Download citation

Publish with us

Policies and ethics