single-rb.php

JRM Vol.35 No.6 pp. 1532-1539
doi: 10.20965/jrm.2023.p1532
(2023)

Development Report:

Simplified System Integration of Robust Mobile Robot for Initial Pose Estimation for the Nakanoshima Robot Challenge

Tomohiro Umetani ORCID Icon, Seo Takeda, Ryusei Yamamoto, and Yuki Shirakata

Department of Intelligence and Informatics, Konan University
8-9-1 Okamoto, Higashinada-ku, Kobe, Hyogo 658-8501, Japan

Received:
June 26, 2023
Accepted:
September 26, 2023
Published:
December 20, 2023
Keywords:
mobile robot, mobile robot challenge, initial localization, expansion resetting, system integration
Abstract

This paper describes a study of the simple system integration of a mobile robot in the Nakanoshima Robot Challenge 2022. To improve the operability of the robot at the start of its journey, we studied the solution to the problem of initial localization during the experimental run and the setting of virtual obstacles on the map to be used by the mobile robot. This method reduces the amount of time and manual operation required to estimate the initial position and orientation of a mobile robot in mobile robot experiments. In this study, a mobile robot is implemented using open-source products such as robot operating system (ROS) and i-Cart mini. Experimental runs in the Extra Challenge of the Nakanoshima Robot Challenge 2022 demonstrate the feasibility of the method.

Map with virtual obstacle data for navigation

Map with virtual obstacle data for navigation

Cite this article as:
T. Umetani, S. Takeda, R. Yamamoto, and Y. Shirakata, “Simplified System Integration of Robust Mobile Robot for Initial Pose Estimation for the Nakanoshima Robot Challenge,” J. Robot. Mechatron., Vol.35 No.6, pp. 1532-1539, 2023.
Data files:
References
  1. [1] S. Yuta, “Tsukuba Challenge: Open Experiments for Autonomous Navigation of Mobile Robots in the City – Activities and Results of the First and Second Stages –,” J. Robot. Mechatron., Vol.30, No.4, pp. 504-512, 2018. https://doi.org/10.20965/jrm.2018.p0504
  2. [2] Y. Hara, T. Tomizawa, H. Date, Y. Kuroda, and T. Tsubouchi, “Tsukuba Challenge 2019: Task Setting and Experimental Results,” J. Robot. Mechatron., Vol.32, No.6, pp. 1104-1111, 2020. https://doi.org/10.20965/jrm.2020.p1104
  3. [3] T. Takubo, S. Aoyagi, Y. Inoue, A. Imazu, and K. Ikoma, “Report of Nakanoshima Challenge 2019,” Proc. 20th SICE System Integration Division Conf., pp. 1937-1938, 2019 (in Japanese).
  4. [4] T. Takubo, “Recommendation of Participating Robotics Challenges,” Proc. 63rd Annual Conf. of the Institute of Systems, Control and Information Engineers, pp. 685-688, 2019 (in Japanese).
  5. [5] S. Tarao, Y. Fujiwara, N. Tsuda, and S. Tanaka, “Prototyping Using a Mobile Robot Platform Equipped with Low-End In-Wheel Motor,” J. Robot. Mechatron., Vol.32, No.6, pp. 1154-1163, 2020. https://doi.org/10.20965/jrm.2020.p1154
  6. [6] S. Hara, T. Shimizu, M. Konishi, R. Yamamura, and S. Ikemoto, “Autonomous Mobile Robot for Outdoor Slope Using 2D LiDAR with Uniaxial Gimbal Mechanism,” J. Robot. Mechatron., Vol.32, No.6, pp. 1173-1182, 2020. https://doi.org/10.20965/jrm.2020.p1173
  7. [7] S. Tanaka and Y. Inoue, “Outdoor Human Detection with Stereo Omnidirectional Cameras,” J. Robot. Mechatron., Vol.32, No.6, pp. 1193-1199, 2020. https://doi.org/10.20965/jrm.2020.p1193
  8. [8] R. Miyagusuku, Y. Arai, Y. Kakigi, T. Takebayashi, A. Fukushima, and K. Ozaki, “Toward Autonomous Garbage Collection Robots in Terrains with Different Elevations,” J. Robot. Mechatron., Vol.32, No.6, pp. 1164-1172, 2020. https://doi.org/10.20965/jrm.2020.p1164
  9. [9] J. Xue, Z. Li, M. Fukuda, T. Takahashi, M. Suzuki, Y. Mae, and S. Aoyagi, “Garbage Detection Using YOLOv3 in Nakanoshima Challenge,” J. Robot. Mechatron., Vol.32, No.6, pp. 1200-1210, 2020. https://doi.org/10.20965/jrm.2020.p1200
  10. [10] K. Shigematsu, Y. Konishi, R. Mitsudome, and T. Tsubouchi, “Recognition of Pedestrian Traffic Light at Crosswalk for a Mobile Robot Using Deep Learning,” Trans. of the Society of Instrument and Control Engineers, Vol.54, No.1, pp. 99-110, 2018 (in Japanese). https://doi.org/10.9746/sicetr.54.99
  11. [11] M. Fukuda, T. Takahashi, M. Suzuki, Y. Mae, Y. Arai, and S. Aoyagi, “Proposal of Robot Software Platform with High Sustainability,” J. Robot. Mechatron., Vol.32, No.6, pp. 1219-1228, 2020. https://doi.org/10.20965/jrm.2020.p1219
  12. [12] S. Takeda, R. Yamamoto, Y. Shirakata, and T. Umetani, “Development of Mobile Service Robot from Robotics Laboratory at Konan University for the Nakanoshima Robot Challenge 2022,” Proc. SICE System Integration Division Conf. 2022 (SI 2022), pp. 1170-1173, 2022 (in Japanese).
  13. [13] T. Umetani, Y. Kondo, and T. Tokuda, “Rapid Development of a Mobile Robot for the Nakanoshima Challenge Using a Robot for Intelligent Environment,” J. Robot. Mechatron., Vol.32, No.6, pp. 1211-1218, 2020. https://doi.org/10.20965/jrm.2020.p1211
  14. [14] S. Takeda, T. Okamoto, H. Moriwaki, and T. Umetani, “Development of Mobile Service Robot from Robotics Laboratory at Konan University for the Nakanoshima Robot Challenge 2021,” Proc. SICE System Integration Division Conf. 2021 (SI 2021), pp. 3402-3405, 2021 (in Japanese).
  15. [15] M. Tanaka and K. Kochi, “Initial Position Estimation of a Mobile Robot with a Laser Range Finder by Differential Evolution,” Int. J. Adv. Mechatron. Syst., Vol.5, No.6, pp. 373-382, 2013. https://doi.org/10.1504/IJAMECHS.2013.060020
  16. [16] S. Takeda and T. Umetani, “Initial Localization of Mobile Robot Based on Expansion Resetting Without Manual Pose Adjustment in Robot Challenge Experiment,” J. Robot. Mechatron., Vol.35, No.2, pp. 380-386, 2023. https://doi.org/10.20965/jrm.2023.p0380
  17. [17] R. Ueda, T. Arai, K. Sakamoto, T. Kikuchi, and S. Kamiya, “Expansion Resetting for Recovery from Fatal Error in Monte Carlo Localization: Comparison with Sensor Resetting Methods,” Proc. 2004 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 2481-2486, 2004. https://doi.org/10.1109/IROS.2004.1389781
  18. [18] R. Ueda, T. Arai, K. Asanuma, K. Umeda, and H. Osumi, “Recovery Methods for Fatal Estimation Errors on Monte Carlo Localization,” J. Robotics Society of Japan, Vol.23, No.4, pp. 466-473, 2005 (in Japanese). https://doi.org/10.7210/jrsj.23.466
  19. [19] K. Natsusako, H. Inoue, S. Terato, T. Amano, K. Kubota, H. Goto, S. Shiotani, S. Shimamura, T. Nagashima, R. Ueda, and Y. Hayashibara, “Development Activity of Chiba Institute of Technology Robot Design and Control Laboratory in Tsukuba Challenge 2016,” Proc. SICE System Integration Division Conf. 2016 (SI 2016), pp. 99-104, 2016 (in Japanese).
  20. [20] K. Natsusako, H. Inoue, S. Terato, H. Goto, T. Nagashima, N. Shimamori, R. Suzuki, A. Hashimoto, Y. Fujisawa, R. Ueda, and Y. Hayashibara, “Development Activity of Chiba Institute of Technology Robot Design and Control Laboratory in Tsukuba Challenge 2017,” Proc. SICE System Integration Division Conf. 2017 (SI 2017), pp. 1178-1179, 2017 (in Japanese).
  21. [21] M. Tanaka, M. Wada, T. Umetani, and M. Ito, “Detection of Mobile Objects by Mixture PDF Model for Mobile Robots,” Trans. of the Institute of Systems, Control and Information Engineers, Vol.25, No.11, pp. 308-315, 2012. https://doi.org/10.5687/iscie.25.308
  22. [22] J. Park and J.-W. Jung, “A method to LRF noise filtering for the transparent obstacle in mobile robot indoor navigation environment with straight glass wall,” Proc. 2016 13th Int. Conf. on Ubiquitous Robots and Ambient Intelligence, pp. 194-197, 2016. https://doi.org/10.1109/URAI.2016.7625735
  23. [23] J. Eguchi and K. Ozaki, “Development of Autonomous Mobile Robot Based on Accurate Map in the Tsukuba Challenge 2014,” J. Robot. Mechatron., Vol.27, No.4, pp. 346-355, 2015. https://doi.org/10.20965/jrm.2015.p0346
  24. [24] A. Ravankar, A. Ravankar, Y. Hoshino, and Y. Kobayashi, “Virtual Obstacles for Safe Mobile Robot Navigation,” Proc. 2019 8th Int. Congress on Advanced Applied Informatics, pp. 552-555, 2019. https://doi.org/10.1109/IIAI-AAI.2019.00118
  25. [25] K. Ueno, T. Kinoshita, K. Kobayashi, and K. Watanabe, “Development of a Robust Path-Planning Algorithm Using Virtual Obstacles for an Autonomous Mobile Robot,” J. Robot. Mechatron., Vol.27, No.3, pp. 286-292, 2015. https://doi.org/10.20965/jrm.2015.p0286
  26. [26] T. Eda, T. Hasegawa, S. Nakamura, and S. Yuta, “Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015,” J. Robot. Mechatron., Vol.28, No.4, pp. 461-469, 2016. https://doi.org/10.20965/jrm.2016.p0461
  27. [27] Y. Kanuki and N. Ohta, “Development of Autonomous Robot with Simple Navigation System for Tsukuba Challenge 2015,” J. Robot. Mechatron., Vol.28, No.4, pp. 432-440, 2016. https://doi.org/10.20965/jrm.2016.p0432
  28. [28] T. Ikebe, Y. Cao, S. Takahashi, A. C. Perez, Y. Hayashibara, and R. Ueda, “Challenge to Tsukuba Challenge with a small mobile robot,” Proc. SICE System Integration Division Conf. 2021 (SI 2021), pp. 3390-3393, 2021 (in Japanese).
  29. [29] S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” The MIT Press, Cambridge, Massachusetts, 2005.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024