A Versatile Decentralized 3D Volumetric Fusion for On-line Reconstruction

  • A. Rajput Department of Computer Science, Sukkur IBA University, Pakistan
  • A. Hussain Department of Electrical Engineering, Sukkur IBA University, Pakistan
  • F. Akhtar Department of Computer Science, Sukkur IBA University, Pakistan
  • Z. H. Khand Department of Computer Science, Sukkur IBA University, Pakistan
  • H. Magsi Department of Electrical Engineering, Sukkur IBA University, Pakistan
Volume: 10 | Issue: 6 | Pages: 6584-6588 | December 2020 | https://doi.org/10.48084/etasr.3838


Advancement in depth-sensing technology has allowed mobile robots to visualize the surrounding environment in 3D models. Regardless of the sensing technology (i.e. active, passive, or laser-based), a complete system that integrates recent depth data in previous 3D models in real-time is done by employing Simultaneous Localization And Mapping (SLAM) algorithms followed by a 3D reconstruction engine. Unfortunately, both the SLAM algorithm and the 3D reconstruction engine are usually executed on a single computing device, making the whole system exceptionally costly and heavy and restricting the robot's mobility. This paper proposes a decentralized, modular reconstruction system capable of employing various sensors to facilitate online 3D reconstruction from a resource-limited mobile robot.

Keywords: 3D reconstruction, visualSLAM, depth fusion


Download data is not yet available.


J. Kastrenakes, "Google's Project Tango is shutting down because ARCore is already here," The Verge, Dec. 15, 2017. https://www.theverge.com/2017/12/15/16782556/project-tango-google-shutting-down-arcore-augmented-reality (accessed Dec. 11, 2020).

"Give Your iPad 3D Vision," Structure by Occipital. https://structure.io/ (accessed Dec. 11, 2020).

M. K. Villareal and A. F. Tongco, "Multi-sensor Fusion Workflow for Accurate Classification and Mapping of Sugarcane Crops," Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4085-4091, Jun. 2019. DOI: https://doi.org/10.48084/etasr.2682

M. B. Ayed, L. Zouari, and M. Abid, "Software In the Loop Simulation for Robot Manipulators," Engineering, Technology & Applied Science Research, vol. 7, no. 5, pp. 2017-2021, Oct. 2017. DOI: https://doi.org/10.48084/etasr.1285

O. Kähler, V. A. Prisacariu, C. Y. Ren, X. Sun, P. Torr, and D. Murray, "Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices," IEEE Transactions on Visualization and Computer Graphics, vol. 21, no. 11, pp. 1241-1250, Nov. 2015. DOI: https://doi.org/10.1109/TVCG.2015.2459891

F. Steinbrücker, J. Sturm, and D. Cremers, "Volumetric 3D mapping in real-time on a CPU," in 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 2014, pp. 2021-2028. DOI: https://doi.org/10.1109/ICRA.2014.6907127

M. A. A. Rajput, E. Funk, A. Börner, and O. Hellwich, "Recursive Total Variation Filtering Based 3D Fusion," in International Conference on Signal Processing and Multimedia Applications, Lisbon, Portugal, Dec. 2020, vol. 5, pp. 72-80.

M. Quigley et al., "ROS: An Open-Source Robot Operating System," presented at the ICRA Workshop on Open Source Software, Jan. 2009, vol. 3.

J. Engel, T. Schöps, and D. Cremers, "LSD-SLAM: Large-Scale Direct Monocular SLAM," in Computer Vision - ECCV 2014, 2014, pp. 834-849. DOI: https://doi.org/10.1007/978-3-319-10605-2_54

F. Endres, J. Hess, J. Sturm, D. Cremers, and W. Burgard, "3-D Mapping With an RGB-D Camera," IEEE Transactions on Robotics, vol. 30, no. 1, pp. 177-187, Feb. 2014. DOI: https://doi.org/10.1109/TRO.2013.2279412

J. Engel, J. Stückler, and D. Cremers, "Large-scale direct SLAM with stereo cameras," in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, Sep. 2015, pp. 1935-1942. DOI: https://doi.org/10.1109/IROS.2015.7353631

S. Leutenegger, S. Lynen, M. Bosse, R. Siegwart, and P. Furgale, "Keyframe-based visual-inertial odometry using nonlinear optimization," The International Journal of Robotics Research, vol. 34, no. 3, pp. 314-334, Mar. 2015. DOI: https://doi.org/10.1177/0278364914554813

R. Mur-Artal and J. D. Tardós, "ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras," IEEE Transactions on Robotics, vol. 33, no. 5, pp. 1255-1262, Oct. 2017. DOI: https://doi.org/10.1109/TRO.2017.2705103

B. Curless and M. Levoy, "A volumetric method for building complex models from range images," in Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, New York, NY, USA, Aug. 1996, pp. 303-312. DOI: https://doi.org/10.1145/237170.237269

R. A. Newcombe et al., "KinectFusion: Real-time dense surface mapping and tracking," in 2011 10th IEEE International Symposium on Mixed and Augmented Reality, Basel, Switzerland, Oct. 2011, pp. 127-136. DOI: https://doi.org/10.1109/ISMAR.2011.6162880

T. Whelan, M. Kaess, M. Fallon, H. Johannsson, J. Leonard, and J. McDonald, "Kintinuous: Spatially Extended KinectFusion," MIT, Technical Report MIT-CSAIL-TR-2012-020, Jul. 2012.

M. A. A. Rajput, E. Funk, A. Börner, and O. Hellwich, "Boundless Reconstruction Using Regularized 3D Fusion," in E-Business and Telecommunications, 2017, pp. 359-378. DOI: https://doi.org/10.1007/978-3-319-67876-4_17

M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, "FastSLAM: a factored solution to the simultaneous localization and mapping problem," in Eighteenth national conference on Artificial intelligence, USA, Jul. 2002, pp. 593-598.

W. E. Lorensen and H. E. Cline, "Marching cubes: A high resolution 3D surface construction algorithm," ACM SIGGRAPH Computer Graphics, vol. 21, no. 4, pp. 163-169, Aug. 1987. DOI: https://doi.org/10.1145/37402.37422

A. Geiger, P. Lenz, C. Stiller, and R. Urtasun, "Vision meets robotics: The KITTI dataset," International Journal of Robotics Research, vol. 32, no. 11, pp. 1231-1237, Sep. 2013. DOI: https://doi.org/10.1177/0278364913491297

O. Wasenmüller, M. Meyer, and D. Stricker, "CoRBS: Comprehensive RGB-D benchmark for SLAM using Kinect v2," in 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA, Mar. 2016, pp. 1-7. DOI: https://doi.org/10.1109/WACV.2016.7477636


Abstract Views: 82
PDF Downloads: 48

Metrics Information
Bookmark and Share

Most read articles by the same author(s)