ORB-SLAM accelerated on heterogeneous parallel architectures

Ayoub Mamri; Mohamed Abouzahir; Mustapha Ramzi; Rachid Latif

doi:10.1051/e3sconf/202122901055

All issues

Volume 229 (2021)

E3S Web Conf., 229 (2021) 01055

References

Open Access

Issue		E3S Web Conf. Volume 229, 2021 The 3^rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)


Article Number		01055
Number of page(s)		7
DOI		https://doi.org/10.1051/e3sconf/202122901055
Published online		25 January 2021

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[1] National instrument, introduction to fpga technology: Top 5 benefits, http://www.ni.com/white-paper/6984/en/. 2012. [Google Scholar]

[2] J. Cong, B. Liu, S. Neuendorffer, J. Noguera, K. Vissers, and Z. Zhang. High-level synthesis for fpgas: From prototyping to deployment. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 30(4):473–491, April 2011. I [CrossRef] [Google Scholar]

[3] Khronos Group, “OpenCL-The open standard for parallel programming of heterogeneous systems, ” [Google Scholar]

[4] Li H, Yu D, Kumar A, Tu YC. Performance Modeling in CUDA Streams A Means for HighThroughput Data Processing, Proc IEEE Int Conf Big Data. pp, 301-310, 2014. [PubMed] [Google Scholar]

[5] Sebastian Thrun and John J Leonard. Simultaneous localization and mapping. In Springer handbook of robotics, pages 871–889. Springer, 2008. [CrossRef] [Google Scholar]

[6] Scaramuzza, D., Fraundorfer, F.: Visual odometry: Part i the first 30 years and fundamentals. [Google Scholar]

[7] Abouzahir, M., Elouardi, A., Latif, R., Bouaziz, S., & Tajer, A. (2018). Embedding SLAM algorithms: Has it come of age? Robotics and Autonomous Systems, 100, 14–26. [CrossRef] [Google Scholar]

[8] Nguyen, D.-D., Elouardi, A., Florez, S. A. R., & Bouaziz, S. (2018). HOOFR SLAM System: An Embedded Vision SLAM Algorithm and Its Hardware-Software Mapping-Based Intelligent Vehicles Applications. IEEE Transactions on Intelligent Transportation Systems, 1–16. 8 [Google Scholar]

[9] R. Mur-Artal and J. D. Tardós, “ORB-SLAM2: An open-source SLAM system for monocular, stereo, and RGB-D cameras, ” IEEE Trans. Robot., Vol. 33, no. 5, pp. 1255–1262, 2017. [CrossRef] [Google Scholar]

[10] Shi, X., Cao, L., Wang, D., Liu, L., You, G., Liu, S., & Wang, C. (2018). HERO: Accelerating Autonomous Robotic Tasks with FPGA. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). [Google Scholar]

[11] Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015). ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics, 31(5), 1147–1163. [CrossRef] [Google Scholar]

[12] http://vision.in.tum.de/data/datasets/rgbd-dataset/download [Google Scholar]

[13] R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed., Cambridge, U.K. 2004. [CrossRef] [Google Scholar]

[14] E. Michaelsen, W. V. Hansen, M. Kirchhof, J. Meidow, and U. Stilla, “Estimating the essential matrix: GOODSAC versus RANSAC, ” in Proc. Symp. ISPRS Commission III Photogramm. Comput. Vis. (PCV), Germany, Sep. 2006. [Google Scholar]

[15] Jia, Q., & Zhou, H. Tuning Stencil codes in OpenCL for FPGAs. 2016 IEEE 34th International Conference on Computer Design (ICCD). [Google Scholar]

[16] Altera sdk for OpenCL, Best Practices Guide, https://www.intel.com/content/dam/www/programmable/us/en/pdfs/literature/hb/opencl-sdk/aocl-best-practices-guide.pdf [Google Scholar]

[17] J. Li, G. Deng, W. Zhang, C. Zhang, F. Wang and Y. Liu. Realization of CUDA-based real-time multi-camera visual SLAM in embedded systems. Journal of Real-Time Image Processing. 2019. [Google Scholar]