Abstract
The task of simultaneous localization and mapping (SLAM) allows a mobile robot to localize itself in the unknown environment, while building the map of the surrounding landscape. It is frequently used for the navigation of autonomous mobile robots. Despite the fact that there are plenty available solutions, real applications encounter various application constraints. The present work addresses the subject of the modified fastSLAM application using custom lidar as the detection sensor. Available localization solutions are assessed, their constraints are identified and corresponding solutions are proposed. The algorithm is implemented, tested using simulations and finally applied to the existing mobile platform. Its validation considers various practical aspects of its operation in real-time environment.
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Data availability
The datasets generated during and/or analyzed during the current study are not publicly available due to complexity of the experiments, but are available from the corresponding author on reasonable request.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Bartosz Maziarz. The first draft of the manuscript was written by Paweł D. Domański and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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The authors have no relevant financial or non-financial interests to disclose.The project was funded by POB Research Centre for Artificial Intelligence and Robotics of Warsaw University of Technology within the Excellence Initiative Program—Research University (ID-UB).
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Maziarz, B., Domański, P.D. Customized fastSLAM algorithm: analysis and assessment on real mobile platform. Nonlinear Dyn 110, 669–691 (2022). https://doi.org/10.1007/s11071-022-07633-x
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DOI: https://doi.org/10.1007/s11071-022-07633-x