The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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An Embedded Solution for Fast Navigation and Precise Positioning of Indoor Mobile Robots by Floor Features

바닥 특징점을 사용하는 실내용 정밀 고속 자율 주행 로봇을 위한 싱글보드 컴퓨터 솔루션

  • Kim, Yong Nyeon (Intelligent Robot Engineering, Hanyang University) ;
  • Suh, Il Hong (Electronics and Computer Engineering, Hanyang University)
  • Received : 2019.05.07
  • Accepted : 2019.09.16
  • Published : 2019.11.30
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Abstract

In this paper, an Embedded solution for fast navigation and precise positioning of mobile robots by floor features is introduced. Most of navigation systems tend to require high-performance computing unit and high quality sensor data. They can produce high accuracy navigation systems but have limited application due to their high cost. The introduced navigation system is designed to be a low cost solution for a wide range of applications such as toys, mobile service robots and education. The key design idea of the system is a simple localization approach using line features of the floor and delayed localization strategy using topological map. It differs from typical navigation approaches which usually use Simultaneous Localization and Mapping (SLAM) technique with high latency localization. This navigation system is implemented on single board Raspberry Pi B+ computer which has 1.4 GHz processor and Redone mobile robot which has maximum speed of 1.1 m/s.

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References

  1. D. Droeschel and S. Behnke, "Efficient Continuous-Time SLAM for 3D Lidar-Based Online Mapping," 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, 2018.
  2. W. Hess, D. Kohler, H. Rapp, and D. Andor, "Real-time loop closure in 2D LIDAR SLAM," 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.
  3. M. R. U. Saputra, A. Markham, and N. Trigoni, "Visual SLAM and structure from motion in dynamic environments: A survey," Journal ACM Computing Surveys (CSUR), vol. 51, no. 2, Jun., 2018.
  4. Y. Lu, Z. Xue, and G.-S. Xia, "A survey on vision-based UAV navigation," Geo-spatial Information Science, vol. 21, no. 1, pp. 21-32, 2018. https://doi.org/10.1080/10095020.2017.1420509
  5. Y. Lin, F. Gao, W. Gao, T. Liu, W. Wu, Z. Yang, and S. Shen, "Autonomous aerial navigation using monocular visual-inertial fusion," Journal of Field Robotics, vol. 35, no. 1, pp. 23-51, 2018. https://doi.org/10.1002/rob.21732
  6. P. Cui, X. Gao, S. Zhu, and W. Shao, "Visual navigation using edge curve matching for pinpoint planetary landing," Acta Astronautica, vol. 146, pp. 171-180, May, 2018. https://doi.org/10.1016/j.actaastro.2018.02.033
  7. T. Sayre-McCord, W. Guerra, A. Antonini, J. Arneberg, A. Brown, G. Cavalheiro, Y. Fang, and A. Gorodetsky, "Visualinertial navigation algorithm development using photorealistic camera simulation in the loop," 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, 2018.
  8. R. Mur-Artal, J. M. M. Montiel, and J. D. Tardos, "ORB-SLAM: a versatile and accurate monocular SLAM system," IEEE Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, 2015. https://doi.org/10.1109/TRO.2015.2463671
  9. M. Yazdi and T. Bouwmans, "New trends on moving object detection in video images captured by a moving camera: A survey," Computer Science Review, vol. 28, pp. 157-177, May, 2018. https://doi.org/10.1016/j.cosrev.2018.03.001
  10. J. J. Lugo and A. Zell, "Framework for autonomous on-board navigation with the AR. Drone," Journal of Intelligent & Robotic Systems, vol. 73, no. 1-4, pp. 401-412, Jan., 2014. https://doi.org/10.1007/s10846-013-9969-5
  11. N. Jeong, H. Hwang, and E. T. Matson, "Evaluation of lowcost LiDAR sensor for application in indoor UAV navigation," 2018 IEEE Sensors Applications Symposium (SAS), Seoul, South Korea, 2018.
  12. L. Heng, L. Meier, P. Tanskanen, F. Fraundorfer, and M, Pollefeys, "Autonomous obstacle avoidance and maneuvering on a visionguided mav using on-board processing," 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, 2011.
  13. A. Gongora and J. Gonzalez-Jimenez, "Enhancement of a commercial multicopter for research in autonomous navigation," 2015 23rd Mediterranean Conference on Control and Automation (MED), Torremolinos, Spain, 2015.
  14. F. Blochliger, M. Fehr, M. Dymczyk, T. Schneider, and R. Siegwart, "Topomap: Topological mapping and navigation based on visual slam maps," 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, 2018.
  15. D. W. Ko, Y. N. Kim, J. H. Lee, and I. H. Suh, "A scene-based dependable indoor navigation system," 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016.
  16. J. H. Lee, G. Zhang, J. Lim, and I. H. Suh, "Place Recognition using Straight Lines for Vision-based SLAM," 2013 IEEE International Conference on Robotics and Automation, pp. 3799-3806, Karlsruhe, Germany, 2013.
  17. J. H. Lee, S. Lee, G. Zhang, J. Lim, W. K. Chung, and I. H. Suh, "Outdoor Place Recognition in Urban Environments using Straight Lines," 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.
  18. Z. Chen, A. Jacobson, N. Sünderhauf, B. Upcroft, L. Liu, C. Shen, I. Reid, and M. Milford, "Deep learning features at scale for visual place recognition," 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017.
  19. C. Liang, Y. Tie, L. Qi, and C. Bi, "Deep ViDAR: CNN based $360^{\circ}$ panoramic video system for outdoor robot visual navigation and SLAM," Tenth International Conference on Digital Image Processing (ICDIP 2018), Vol. 10806, 2018.
  20. Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi, "Target-driven visual navigation in indoor scenes using deep reinforcement learning," 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017.
  21. N. Smolyanskiy, A. Kamenev, J. Smith, and S. Birchfield, "Toward low-flying autonomous MAV trail navigation using deep neural networks for environmental awareness," 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, 2017.
  22. Y. Zhuang, Z. Syed, Y. Li, and N. El-Sheimy, "Evaluation of two WiFi positioning systems based on autonomous crowdsourcing of handheld devices for indoor navigation," IEEE Transactions on Mobile Computing, vol. 15, no. 8, pp. 1982-1995, Aug., 2016. https://doi.org/10.1109/TMC.2015.2451641
  23. W. Y. Jeong and K. M. Lee. "CV-SLAM: A new ceiling visionbased SLAM technique," 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, Alta, Canada, 2005.
  24. C. Gamallo, M. Mucientes, and C. V. Regueiro, "Omnidirectional visual SLAM under severe occlusions," Robotics and Autonomous Systems, vol. 65, pp. 76-87, Mar., 2015. https://doi.org/10.1016/j.robot.2014.11.008