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Particle filter — Scan matching SLAM recovery under kinematic model failures

Aristeidis G. Thallas, Emmanouil Tsardoulias, Loukas Petrou

发表年份
2016
引用次数
2

摘要

Simultaneous localization and mapping comprises two highly correlated procedures, which renders it a greatly difficult problem. Its difficulty is further increased due to the high levels of uncertainty introduced by both the environment and the robot's sensors and actuators. In the current paper we present methods to recover from extreme situations where kinematic model failures are observed - robot slipping and movement obstruction - that result in erroneous localizations, leading to complete SLAM method failures.

关键词

Particle filterKinematicsSlippingRobotComputer scienceArtificial intelligenceActuatorComputer visionSimultaneous localization and mappingMatching (statistics)

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