IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Implementation of Wheelchair Robot Applying SLAM and Global Path Planning Methods Suitable for Indoor Autonomous Driving

실내 자율주행에 적합한 SLAM과 전역경로생성 방법을 적용한 휠체어로봇 구현

  • Received : 2021.10.16
  • Accepted : 2021.12.09
  • Published : 2021.12.31
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Abstract

This paper presents how to create a 3D map and solve problems related to generating a global path planning for navigation. Map creation and localization were performed using the RTAB-Map package to create a 3D map of the environment. In addition, when the target point is within the obstacle space, the problem of not generating a global path was solved using the asr_navfn package. The performance of the proposed system is validated through experiments with a wheelchair-type robot.

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Acknowledgement

본 논문은 산업통상자원부 산업기술혁신사업 '가변형 밀착구조를 가진 신체 약자 생활자립형 서비스 로봇 개발(No. 20004720)'의 지원을 받아 연구되었음.

References

  1. https://ko.wikipedia.org/wiki/SLAM
  2. N. Kwak, B.-H. Lee, K. Yokoi, "Result Representation of Rao-Blackwellized Particle Filter for Mobile Robot SLAM," Journal of Korea Robotics Society, Vol. 3, No. 4, pp. 308-314, 2008 (in Korean).
  3. H. S. Kim, J. W. Kam, S. S. Hwang, "An Evaluation System to Determine the Completeness of a Space map Obtained by Visual SLAM," Korea Multimedia Society, Vol. 22, No. 4, pp. 417-423, 2019 (in Korean).
  4. S. Thrun, M. Montemerlo, "The Graph SLAM Algorithm with Applications to Large-scale Mapping of Urban Structures," International Journal of Robotics Research, Vol. 25, No. 5-6, pp. 403-429, 2006. https://doi.org/10.1177/0278364906065387
  5. J. B. Song, S. Y. Hwang, "Past and State-of-the-art SLAM Technologies," Journal of Institute of Control, Robotics and Systems, Vol. 20, No. 3, pp. 372-379, 2014 (in Korean). https://doi.org/10.5302/J.ICROS.2014.14.9024
  6. R. Mur-Artal, J. M. M. Montiel, J. D. Tardos. "ORB-SLAM: a Versatile and Accurate Monocular SLAM System." IEEE Tran. Robotics, Vol. 31. No. 5, pp. 1147-1163, 2015 https://doi.org/10.1109/TRO.2015.2463671
  7. https://www.ros.org/
  8. https://github.com/introlab/rtabmap_ros
  9. N. Ragot, R. Khemmar, A. Pokala, R. Rossi, J. Y. Ertaud, "Benchmark of Visual Slam Algorithms: Orb-slam2 vs Rtab-map," International Conference on Emerging Security Technologies, pp. 1-6, 2019.
  10. https://github.com/asr-ros/asr_navfn
  11. M. Al-Nuaimi, S. Wibowo, H. Qu, J. Aitken, S. Veres, "Hybrid Verification Technique for Decision-making of Self-driving Vehicles," Journal of Sensor and Actuator Networks, Vol. 10, No. 3, pp. 42, 2021. https://doi.org/10.3390/jsan10030042
  12. https://edward0im.github.io/engineering/2020/09/08/pose-graph-optimization/
  13. https://en.wikipedia.org/wiki/Bag-of-words_model_in_computer_vision
  14. S. Byeon, J. Park, "A Resampling Method to Improve the Performance of AMCL Under a few Features Environment." Workshop of Korean Institute of Electrical Engineers, pp. 162-165, 2021 (in Korean).
  15. M. Labbe, F. Michaud, "Long-term Online Multi-session Graph-based SPLAM with Memory Management," Autonomous Robots, Vol. 42, No. 6, pp. 1133-1150, 2018. https://doi.org/10.1007/s10514-017-9682-5
  16. http://wiki.ros.org/navfn
  17. https://mattlee.tistory.com/50
  18. http://wiki.ros.org/rotate_recovery