Mobile robot indoor map building and localization using binocular vision

Authors: Bai Caiyan
Published in issue: #11(28)/2018
DOI: 10.18698/2541-8009-2018-11-405
Category: Mechanical Engineering and Machine Science | Chapter: Robots, Mechatronics, and Robotic Systems
Keywords: mobile robot, map building, robot localization, coordinate transformation, correlation function
Published: 16.11.2018

The paper considers the problem of mobile robot indoor map building and localization using binocular vision system located on the robot itself. The map of a room is built with point clouds obtained from a camera during preliminary observation. It is assumed that the position and orientation of the robot and camera are known. The robot can determine its coordinates at any point of the room. To that end the fragment of the map with the given point has to be located using the vision system. The maximum of cross-correlation function between two signal sources is calculated in order to locate the fragment on the map. After that the coordinates of the mobile robot are calculated using location of the fragment.

References

[1] Yudin D.A., Protsenko V.V., Postol’skiy G.G., Kizhuk A.S., Magergut V.Z. Computer vision system for automatic orientation and positioning of mobile robot. Robototekhnika i tekhnicheskaya kibernetika [Robotics and Technical Cybernetics], 2014, no. 1(2), pp. 70–75.

[2] Noskov V.P., Noskov A.V. Mobile robot’s navigation by means of 3-d laser images. Mekhatronika, avtomatizatsiya, upravlenie, 2005, no. 12, pp. 16–21.

[3] Volodin Yu.S. Televizionnaya sistema ob’’emnogo zreniya dlya upravleniya dvizheniem mobil’nogo robota. Avtoref. diss. kand. tekh. nauk [Stereovision TV system for control on mobile robot. Abs. kand. tech. sci. diss.]. Moscow, Bauman Press, 2011, 16 p.

[4] Gerasimov V.N., Mikhaylov B.B. Reshenie zadachi lokalizatsii mobil’nogo robota v pomeshchenii [Solving localization problem for mobile robot in a room]. Tr. XXII mezhd. nauch.-tekh. konf. “Ekstremal’naya robototekhnika” [Proc. XXII Int. sci.-tech. conf. “Extremal robotics”]. Sankt-Petersburg, Politekhnika-servis publ., 2011, pp. 441–449.

[5] Mikhaylov B.B. Ispol’zovanie sistem tekhnicheskogo zreniya dlya upravleniya mobil’nymi robotami [Using technical vision systems for mobile robots control]. 10 vseross. mul’tikonf. po problemam upravleniya [10 Russ. Multiconf. On control problems]. Rostov-na-Donu, Tagarog, SFEDU publ., 2017, pp. 230–232.

[6] Shapiro L.G., Stockman G.S. Computer vision. Pearson, 2001, 608 p. (Russ. ed.: Komp’yuternoe zrenie. Moscow, BINOM. Laboratoriya znaniy publ., 2006, 752 p.)

[7] Dunn P.F. Measurement and data analysis for engineering and science. McGraw–Hill, 2005, 540 p.

[8] Forsyth D.A., Ponce J. Computer vision: a modern approach. Pearson, 2003. 792 p. (Russ. ed.: Komp’yuternoe zrenie. Sovremennyy podkhod. Moscow, Vil’yams publ., 2004, 928 p.)

[9] Press H.W., Teukolsky A.S., Vetterling T.W., Flannery P.B. Numerical recipes: the art of scientific computing. Cambridge, 2007, pp. 776–780.

[10] Korn G., Korn T. Mathematical handbook for scientists and engineers. McGraw Hill, 1961, 943 p. (Russ. ed.: Spravochnik po matematike. Moscow, Nauka publ., 1974, 832 p.)

[11] Moshkin V.I., Petrov V.S., Titov V.S., Yakushenkov Yu.G. Tekhnicheskoe zrenie robotov [Robot technical vision]. Moscow, Mashinostroenie publ., 1990, 272 p.