方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Simultaneous Localization and Mapping
分类方法记录 · ml-model / control-theory
- 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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