Araştırma Makalesi
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İHA'ların İç Mekan Otonom Navigasyonu için ORB-SLAM Tabanlı 2D Ortamın Yeniden Yapılandırılması

Yıl 2020, Ejosat Özel Sayı 2020 (ICCEES), 466 - 472, 05.10.2020
https://doi.org/10.31590/ejosat.819620

Öz

Bu yazıda, insansız hava araçları için basit ve ekonomik ancak verimli bir otonom haritalama ve navigasyon sistemi sunulmaktadır. Bu sistemi gerçekleştirmek için üç modül uygulanmıştır. İlk modül, dronda otonom olarak gezinirken ortamın 3 boyutlu bir modelini oluşturur ve ORB-SLAM adı verilen en iyi monoküler SLAM algoritmalarından birine dayanır. Sistemin otonom navigasyonu için görsel tabanlı bir hat izleme yöntemi önerilmiştir. Daha sonra, ikinci modül, 3 boyutlu haritanın 2 boyutlu ızgara haritasına gerçek zamanlı dönüşümünü gerçekleştirir. 3B'den 2B'ye harita dönüştürme çalışmalarının çoğu, ikisinin ortasında oktomaplar kullanırken, herhangi bir orta bileşene ihtiyaç duymadan 3B haritayı doğrudan 2B'ye dönüştüren eşik tabanlı bir yöntem sunuyoruz. Son olarak, üçüncü modül, dronu yapılandırılmış 2B ızgara haritasında hedef pozuna götürmek için A* yol planlama algoritmasını kullanır. Bu modül, bu görevi tamamlamak için monoküler kamera bilgileriyle birlikte yalnızca IMU destekli Uyarlanabilir Monte Carlo Konumlandırmasını(AMCL) kullanır. Deney sonuçları, önerilen sistemin yalnızca monoküler bir kamera ve üzerinde sınırlı işlem kaynakları bulunan düşük maliyetli drone'larda kullanılmak için yeterince verimli olduğunu göstermektedir.

Kaynakça

  • Mur-Artal, Raul, and Juan D. Tardós. "Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras." IEEE Transactions on Robotics 33.5 (2017): 1255-1262.
  • Gálvez-López, Dorian, and Juan D. Tardos. "Bags of binary words for fast place recognition in image sequences." IEEE Transactions on Robotics 28.5 (2012): 1188-1197.
  • Quigley, Morgan, et al. "ROS: an open-source Robot Operating System." ICRA workshop on open source software. Vol. 3. No. 3.2. 2009.
  • Durdu, Akif, and Mehmet Korkmaz. "Autonomously simultaneous localization and mapping based on line tracking in a factory-like environment." Advances in Electrical and Electronic Engineering 17.1 (2019): 45-53.
  • Chatila, Raja, and Jean-Paul Laumond. "Position referencing and consistent world modeling for mobile robots." Proceedings. 1985 IEEE International Conference on Robotics and Automation. Vol. 2. IEEE, 1985.
  • Harris, Christopher G., and J. M. Pike. "3D positional integration from image sequences." Image and Vision Computing 6.2 (1988): 87-90.
  • Smith, Randall, Matthew Self, and Peter Cheeseman. "Estimating uncertain spatial relationships in robotics." Autonomous robot vehicles. Springer, New York, NY, 1990. 167-193.
  • Doucet, Arnaud, et al. "Rao-Blackwellised particle filtering for dynamic Bayesian networks." arXiv preprint arXiv:1301.3853 (2013).
  • Martinez-Cantin, Ruben, and José A. Castellanos. "Unscented SLAM for large-scale outdoor environments." 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005.
  • Montemerlo, M. "A Factored Solution to the Simultaneous Localization and Mapping Problem with Unknown Data Association." Ph. D. thesis, Carnegie Mellon University (2003).
  • Kim, Chanki, Rathinasamy Sakthivel, and Wan Kyun Chung. "Unscented FastSLAM: a robust and efficient solution to the SLAM problem." IEEE Transactions on robotics 24.4 (2008): 808-820.
  • Kurt-Yavuz, Zeyneb, and Sirma Yavuz. "A comparison of EKF, UKF, FastSLAM2. 0, and UKF-based FastSLAM algorithms." 2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES). IEEE, 2012.
  • Mur-Artal, Raul, and Juan D. Tardós. "Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras." IEEE Transactions on Robotics 33.5 (2017): 1255-1262.
  • Goeddel, Robert, et al. "FLAT2D: Fast localization from approximate transformation into 2D." 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016.
  • Huesman, Jacob. "Converting 3D Point Cloud Data into 2D Occupancy Grids suitable for Robot Applications." NDSU EXPLORE: Undergraduate Excellence in Research and Scholarly Activity (2015).
  • Beutel, Alex, Thomas Mølhave, and Pankaj K. Agarwal. "Natural neighbor interpolation based grid DEM construction using a GPU." Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2010.
  • Fankhauser, Péter, and Marco Hutter. "A universal grid map library: Implementation and use case for rough terrain navigation." Robot Operating System (ROS). Springer, Cham, 2016. 99-120.
  • Thrun, Sebastian. "Learning occupancy grid maps with forward sensor models." Autonomous robots 15.2 (2003): 111-127.

ORB-SLAM-based 2D Reconstruction of Environment for Indoor Autonomous Navigation of UAVs

Yıl 2020, Ejosat Özel Sayı 2020 (ICCEES), 466 - 472, 05.10.2020
https://doi.org/10.31590/ejosat.819620

Öz

In this paper, a simple and economic yet efficient autonomous mapping and navigation system for unmanned aerial vehicles is presented. In order to realize this system, three modules have been implemented. First module constructs a 3D model of the environment while autonomously navigating the drone and is based on one of the top monocular SLAM algorithms called ORB-SLAM. For the autonomous navigation of the system a visual-based line tracking method is proposed. Afterwards, the second module performs a real time transformation of the 3D map to 2D grid map. While most of the 3D to 2D map conversion studies use octomaps in the middle of two, we present a threshold-based method that directly converts the 3D map to 2D without need for any middle component. Finally, third module uses A* path planning algorithm to navigate the drone to the goal pose in the constructed 2D grid map. This module uses only IMU-aided Adaptive Monte Carlo localization (AMCL) combined with monocular camera information to complete this task. The experimentation results indicate that the proposed system is adequately efficient to be used in the low-cost drones that have only a monocular camera and limited processing resources on them.

Kaynakça

  • Mur-Artal, Raul, and Juan D. Tardós. "Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras." IEEE Transactions on Robotics 33.5 (2017): 1255-1262.
  • Gálvez-López, Dorian, and Juan D. Tardos. "Bags of binary words for fast place recognition in image sequences." IEEE Transactions on Robotics 28.5 (2012): 1188-1197.
  • Quigley, Morgan, et al. "ROS: an open-source Robot Operating System." ICRA workshop on open source software. Vol. 3. No. 3.2. 2009.
  • Durdu, Akif, and Mehmet Korkmaz. "Autonomously simultaneous localization and mapping based on line tracking in a factory-like environment." Advances in Electrical and Electronic Engineering 17.1 (2019): 45-53.
  • Chatila, Raja, and Jean-Paul Laumond. "Position referencing and consistent world modeling for mobile robots." Proceedings. 1985 IEEE International Conference on Robotics and Automation. Vol. 2. IEEE, 1985.
  • Harris, Christopher G., and J. M. Pike. "3D positional integration from image sequences." Image and Vision Computing 6.2 (1988): 87-90.
  • Smith, Randall, Matthew Self, and Peter Cheeseman. "Estimating uncertain spatial relationships in robotics." Autonomous robot vehicles. Springer, New York, NY, 1990. 167-193.
  • Doucet, Arnaud, et al. "Rao-Blackwellised particle filtering for dynamic Bayesian networks." arXiv preprint arXiv:1301.3853 (2013).
  • Martinez-Cantin, Ruben, and José A. Castellanos. "Unscented SLAM for large-scale outdoor environments." 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005.
  • Montemerlo, M. "A Factored Solution to the Simultaneous Localization and Mapping Problem with Unknown Data Association." Ph. D. thesis, Carnegie Mellon University (2003).
  • Kim, Chanki, Rathinasamy Sakthivel, and Wan Kyun Chung. "Unscented FastSLAM: a robust and efficient solution to the SLAM problem." IEEE Transactions on robotics 24.4 (2008): 808-820.
  • Kurt-Yavuz, Zeyneb, and Sirma Yavuz. "A comparison of EKF, UKF, FastSLAM2. 0, and UKF-based FastSLAM algorithms." 2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES). IEEE, 2012.
  • Mur-Artal, Raul, and Juan D. Tardós. "Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras." IEEE Transactions on Robotics 33.5 (2017): 1255-1262.
  • Goeddel, Robert, et al. "FLAT2D: Fast localization from approximate transformation into 2D." 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016.
  • Huesman, Jacob. "Converting 3D Point Cloud Data into 2D Occupancy Grids suitable for Robot Applications." NDSU EXPLORE: Undergraduate Excellence in Research and Scholarly Activity (2015).
  • Beutel, Alex, Thomas Mølhave, and Pankaj K. Agarwal. "Natural neighbor interpolation based grid DEM construction using a GPU." Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2010.
  • Fankhauser, Péter, and Marco Hutter. "A universal grid map library: Implementation and use case for rough terrain navigation." Robot Operating System (ROS). Springer, Cham, 2016. 99-120.
  • Thrun, Sebastian. "Learning occupancy grid maps with forward sensor models." Autonomous robots 15.2 (2003): 111-127.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Abdullah Yusefı 0000-0001-7557-8526

Akif Durdu 0000-0002-5611-2322

Cemil Sungur 0000-0003-2340-6225

Yayımlanma Tarihi 5 Ekim 2020
Yayımlandığı Sayı Yıl 2020 Ejosat Özel Sayı 2020 (ICCEES)

Kaynak Göster

APA Yusefı, A., Durdu, A., & Sungur, C. (2020). ORB-SLAM-based 2D Reconstruction of Environment for Indoor Autonomous Navigation of UAVs. Avrupa Bilim Ve Teknoloji Dergisi466-472. https://doi.org/10.31590/ejosat.819620