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Simultaneous Localization and Mapping/Evidence
Method evidence record

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.

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Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Simultaneous Localization and Mapping
Taxonomic method record · 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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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyExtended Kalman Filtermachine-suggested · Relational suggestion, not evidence.See alsoParticle Filtermachine-suggested · Relational suggestion, not evidence.Same method familyUnscented Kalman Filtermachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

3 recorded citations, copied from the method source record.

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