Abstract
The precise positioning of mobile systems is a prerequisite for any autonomous behavior, in an industrial environment as well as for field robotics. The paper describes the set up for an experimental platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. Two approaches are compared. First, a local method based on point cloud matching and integration of inertial measurement units is evaluated. Subsequent matching makes it possible to create a three-dimensional point cloud that can be used as a map in subsequent runs. The second approach is a full SLAM algorithm, based on graph relaxation models, incorporating the full sensor suite of odometry, inertial sensors, and 3D laser scan data.
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This paper has been produced within the framework of the ERASMUS + project Geothermal & Solar Skills Vocational Education and Training (GSS-VET).
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Hensel, S., Marinov, M.B., Kehret, C., Stefanova-Pavlova, M. (2020). Experimental Set-up for Evaluation of Algorithms for Simultaneous Localization and Mapping. In: Yilmaz, M., Niemann, J., Clarke, P., Messnarz, R. (eds) Systems, Software and Services Process Improvement. EuroSPI 2020. Communications in Computer and Information Science, vol 1251. Springer, Cham. https://doi.org/10.1007/978-3-030-56441-4_32
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DOI: https://doi.org/10.1007/978-3-030-56441-4_32
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