Simultaneous Localization and Mapping
Simultaneous Localization and Mapping (SLAM) is the problem of enabling a mobile robot to build a map of its environment while simultaneously determining its own location within that map using noisy sensor measurements. Formulated by Durrant-Whyte and Bailey in 2006, SLAM is fundamental to autonomous robotics, enabling robots to navigate and explore unknown environments without prior maps or external positioning systems.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Durrant-Whyte, H., & Bailey, T. (2006). Simultaneous localization and mapping (SLAM): Part I. IEEE Robotics & Automation Magazine, 13(2), 99-110. · DOI 10.1109/MRA.2006.1638022
- Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic Robotics. MIT Press. · URL
- Dellaert, F., & Kaess, M. (2012). Square root SAM: Simultaneous localization and mapping via square root factor graphs. International Journal of Robotics Research, 25(12), 1181-1203. · URL
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