Penerapan SLAM Gmapping dengan Robot Operating System Menggunakan Laser Scanner pada Turtlebot

Aulia Rahman

Abstract


The manouver ability from one place to another in order to accomplish some tasks safely is a basic requirement of mobile robotics. Current robotic’s navigation systems require a ’real world’ map data, acquired by on-board sensors, to carry out simultaneous localisation and navigation (SLAM) algorithm. There are several SLAM algorithms. In this article we used SLAM gmapping using robot operating system (ROS) and laser scanner. The gmapping slam algorithm used particle filter method to localize robot pose within the environment and generate 2D occupancy grid map. The map is in gray-scale informed the free space, wall, and unexplored space. The implementation of gmapping slam conducted with turtlebot 3 from Robotics as well as 3D simulation using gazebo. 


Keywords


Robot Operating System (ROS); Gmapping slam; Laser scanner; Turtlebot

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C. Badue, R. Guidolini, R. V. Carneiro, P. Azevedo, V. B. Cardoso, A. Forechi, L. F. R. Jesus, R. F. Berriel, T. M. Paixão, F. W. Mutz, T. Oliveira-Santos, and A. F. de Souza, “Self-driving cars: A survey,” CoRR, vol. abs/1901.04407, 2019.

S. Verghese, “Self-driving cars and lidar,” in Conference on Lasers and Electro-Optics. Optical Society of America, 2017, p. AM3A.1.

R. W. Wolcott and R. M. Eustice, “Visual localization within lidar maps for automated urban driving,” in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep. 2014, pp. 176–183.

H. Masuzawa, J. Miura, and S. Oishi, “Development of a mobile robot for harvest support in greenhouse horticulture — person following and mapping,” in 2017 IE- EE/SICE International Symposium on System Integration (SII), Dec 2017, pp. 541–546.

Y. Onishi, T. Yoshida, H. Kurita, T. Fukao, H. Arihara, and A. Iwai, “An automated fruit harvesting robot by using deep learning,” ROBOMECH Journal, vol. 6, no. 1, pp. 13-20, Nov 2019.

M. Firdaus, M. Syaryadhi, and A. Rahman, “Pengendalian robot mobil otonom pemotong rumput menggunakan metode logika fuzzy,” Karya Ilmiah Teknik Elektro, vol. 2, no. 2, 2017.

S. Kohlbrecher, J. Meyer, T. Graber, K. Petersen, U. Kli- ngauf, and O. von Stryk, “Hector open source modules for autonomous mapping and navigation with rescue robots,” in RoboCup 2013: Robot World Cup XVII, S. Behnke, M. Veloso, A. Visser, and R. Xiong, Eds. Berlin, Hei- delberg: Springer Berlin Heidelberg, 2014, pp. 624–631.

S. Sausan, B. Sakti, H. Leo, A. Yuliani, I. Permatasari, A. Rahman, and M. Syaryadhi, “Robot pointer sebagai penunjuk jalan tim sar untuk mempermudah pencarian korban bencana gempa,” Jurnal Rekayasa Elektrika, vol. 13, no. 2, p. 112-118, Aug 2017.

J. J. Leonard and H. F. Durrant-Whyte, “Simultaneous map building and localization for an autonomous mobile robot,” in Proceedings IROS ’91: IEEE/RSJ International Workshop on Intelligent Robots and Systems ’91, Nov 1991, vol.3, pp. 1442–1447.

H. Choset and K. Nagatani, “Topological simultaneous localization and mapping (slam): toward exact localization without explicit localization,” IEEE Transactions on Robotics and Automation, vol. 17, no. 2, pp. 125–137, April 2001.

G. Grisetti, C. Stachniss, and W. Burgard, “Improving grid-based slam with rao-blackwellized particle filters by adaptive proposals and selective resampling,” in Pro- ceedings of the 2005 IEEE International Conference on Robotics and Automation, April 2005, pp. 2432–2437.

W. Lin, J. Hu, H. Xu, C. Ye, X. Ye, and Z. Li, “Graph-based slam in indoor environment using corner feature from laser sensor,” 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC), May 2017.

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.

C. Brand, M. J. Schuster, H. Hirschmuller, and M. Suppa, “Stereovision based obstacle Mapping for indoor/outdoor slam,” 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2014, pp. 1846-1853.

R. Mur-Artal, J. M. M. Montiel, and J. D. Tardós, “Orb- slam: A versatile and accurate monocular slam system,” IEEE Transactions on Robotics, vol. 31, no. 5, pp. 1147– 1163, Oct 2015.

R. Mur-Artal and J. D. Tardos, “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.

P. Corke, Robotics, vision and control: fundamental algorithms in MATLAB® second, completely revised. Springer, 2017.

G. Grisetti, C. Stachniss, and W. Burgard, “Improved techniques for grid mapping with rao-blackwellized particle filters,” IEEE transactions on Robotics, vol. 23, no. 1, pp. 34–46, 2007.

M. Quigley, K. Conley, B. P. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A. Y. Ng, “Ros: an open-source robot operating system,” in ICRA Workshop on Open Source Software, 2009.

Y. Pyo, H. Cho, L. J. Jung, and D. Lim, ROS Robot Programming (English). ROBOTIS, 12 2017. [Online]. Available: http://community.robotsource.org/t/download-the-ros-robotprogramming-book-for-free/51.

E. Yurtsever, J. Lambert, A. Carballo, and K. Takeda, “A survey of autonomous driving: Common practices and emerging technologies,” CoRR, vol. abs/1906.05113, 2019.

S. Thrun, W. Burgard, and D. Fox, Probabilistic robotics. MIT press Cambridge, 2000.




DOI: https://doi.org/10.17529/jre.v16i2.16491

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