Using Bee Algorithm for Lidar Data Comparison in the Problem of Mobile Robots Navigatio

Authors

  • A. I. Abramov
  • I. V. Abramov
  • T. A. Mazitov
  • A. M. Palmov

Keywords:

ICP, swarm algorithms, bee algorithm, localization, mapping

Abstract

An innovative algorithm for laser scans comparison in problem of localization and mapping is considered. The algorithm is based on the comparison of point clouds with a bee swarm algorithm. The structure of the algorithm for implementation on multiprocessor computing devices is developed. Experimental testing of the algorithm proved its high efficiency by the criterion of performance.

References

Leonard J. J., Durrant-Whyte H. F. Simultaneous map building and localization for an autonomous mobile robot // Intelligent Robots and Systems' 91.'Intelligence for Mechanical Systems, Proceedings IROS'91. IEEE/RSJ International Workshop on. - IEEE, 1991. - С. 1442-1447.

Gallegos G., Rives P. Indoor SLAM based on composite sensor mixing laser scans and omnidirectional images // Robotics and Automation (ICRA), 2010 IEEE International Conference on. - IEEE, 2010. - С. 3519-3524.

SLAM in a dynamic large outdoor environment using a laser scanner / Zhao H. [at al.] // Robotics and Automation, 2008. ICRA 2008. IEEE International Conferenceon. - IEEE, 2008. - С. 1455-1462.

Marshall J. A., Barfoot T. D. Design and field testing of an autonomous underground tramming system //Field and Service Robotics. - Springer Berlin Heidelberg, 2008. - С. 521-530.

Marshall J., Barfoot T., Larsson J. Autonomous underground tramming for center-articulated vehicles // Journal of Field Robotics. - 2008. - Т. 25, № 6-7. - С. 400-421.

Ribas D. et al. Underwater SLAM in man-made structured environments // Journal of Field Robotics. - 2008. - Т. 25, № 11-12. - С. 898-921.

A flexible and scalable slam system with full 3d motion estimation / Kohlbrecher S. [et al.] // Safety, Security, and Rescue Robotics (SSRR), 2011 IEEE International Symposium. - IEEE, 2011. - С. 155-160.

OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems / Wurm K. M. [et al.] // Proc. of the ICRA 2010 workshop on best practice in 3D perception and modeling for mobile manipulation. - 2010. - Т. 2.

Chen Y., Medioni G. Object modelling by registration of multiple range images //Image and vision computing. - 1992. - Т. 10, № 3. - С. 145-155.

Besl P. J., McKay N. D. Method for registration of 3-D shapes // Robotics-DL tentative. - International Society for Optics and Photonics, 1992. - С. 586-606.

Beni G., Wang J. Swarm intelligence in cellular robotic systems //Robots and Biological Systems: Towards a New Bionics. - Springer Berlin Heidelberg, 1993. - С. 703-712.

Karaboga D., Akay B. A comparative study of artificial bee colony algorithm // Applied Mathematics and Computation. - 2009. - Т. 214, № 1. - С. 108-132.

Rusinkiewicz S., Levoy M. Efficient variants of the ICP algorithm // 3-D Digital Imaging and Modeling, 2001. Proceedings. Third International Conference on. - IEEE, 2001. - С. 145-152.

Published

30.06.2016

How to Cite

Abramov А. И., Abramov И. В., Mazitov Т. А., & Palmov А. М. (2016). Using Bee Algorithm for Lidar Data Comparison in the Problem of Mobile Robots Navigatio. Vestnik IzhGTU Imeni M.T. Kalashnikova, 19(2), 101–104. Retrieved from https://izdat.istu.ru/index.php/vestnik/article/view/3244

Issue

Section

Informatics, Computer Science and Control (only archive)