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Mapping of Rescue Environment Based on NDT Scan Matching

Jin Liang Li, You Xia Sun

发表年份
2013
引用次数
3

摘要

This paper studied the mapping problem for rescue robots based on laser scan matching and extend Kalman filtering (EKF). Because of the non-structural rescue environments, it is hard to extract typical features. Scan matching method based on normal distribution transform (NDT) can avoid the hard feature extraction problem by estimation of the probability distribution of laser scan data. By fusing NDT scan matching with EKF framework, the NDT-EKF SLAM algorithm was proposed, which can effectively and precisely build maps for rescue environment. Experiment results show that NDT-EKF SLAM algorithm is more precise than algorithms based solely on scan-matching.

关键词

Extended Kalman filterNondestructive testingMatching (statistics)Simultaneous localization and mappingArtificial intelligenceRescue robotComputer visionFeature (linguistics)Computer scienceKalman filter

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