Abstract
Simultaneous localization and mapping (SLAM) of an unknown environment is a primary requirement for any autonomous robot. In this paper we present a cost-effective, robust, and integrated software/hardware SLAM solution for 2D mapping of large indoor environments. The presented SLAM solution consists of a robotic platform, referred as MapperBot, and an effective implementation of SLAM algorithm, referred as iSCAN. MapperBot is built using commercial of-the-shelf components with an open-source software/hardware design presented in this paper. The SLAM algorithm iSCAN is based on a highly robust laser-scan matching technique, incorporating Rao-Blackwellized particle filter as a mean to increase its accuracy. As a result, a minimal number of particles is required, and the computer processing time is dramatically reduced. MapperBot/iSCAN solution is fully integrated with the Matlab environment, thus providing researchers, students and developers a quick entry into the realm of the SLAM.
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Notes
Wheel encoders are sensors that provide the angular position of the wheel in the form of digital pulses or a code word.
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Al-Hourani, A., Ristic, B. MapperBot/iSCAN: open-source integrated robotic platform and algorithm for 2D mapping. Int J Intell Robot Appl 4, 44–56 (2020). https://doi.org/10.1007/s41315-020-00118-3
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DOI: https://doi.org/10.1007/s41315-020-00118-3