Simultaneous Localization and Mapping: la soluzione chiave per il rilievo in movimento


  • Eleonora Maset
  • Lorenzo Scalera

Parole chiave:

Geomatica, slam, rilievo, robotica


Many of us, looking at a latest robot vacuum cleaner generation move for home, you definitely are ask yourself how this appliance “smart” is able independently to clean all surfaces, avoiding the obstacles present in the area. The answer is enclosed in the acronym SLAM (Simultaneous Localisation and Mapping), i.e. in the technique that allows a moving robot, equipped with sensors, to build the map of the environment that surrounds it and, at the same time, to use such a map to determine its location, such as shown in the sequence of images of Figure 1.

Riferimenti bibliografici

Durrant-Whyte, H, e Bailey, T., 2006. Simultaneous Localization and Mapping (SLAM): Part I, The Essential Algorithms. Robotics & Automation Magazine, 13.

Grisetti, G., Kümmerle, R., Stachniss, C., Burgard,W., 2010. A tutorial on graph-based SLAM. IEEE Intelligent Transportation Systems Magazine, 2(4), pp. 31–43.

Tiozzo Fasiolo D., Scalera L., Maset E., Gasparetto A., 2022. Experimental evaluation and comparison of LiDAR SLAM algorithms for mobile robotics. In: Niola, V., Gasparetto, A., Quaglia, G., Carbone, G. (eds) Advances in Italian Mechanism Science. IFToMM Italy 2022. Mechanisms and Machine Science, 122, pp. 795 – 803.




Come citare

Maset, E., & Scalera, L. (2023). Simultaneous Localization and Mapping: la soluzione chiave per il rilievo in movimento. GEOmedia, 26(5). Recuperato da