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A robust SLAM algorithm using hybrid map approach

Sung-Hyeon Joo, Ung-Hee Lee, Tae‐Yong Kuc, Jong-Koo Park

发表年份
2018
引用次数
5

摘要

This paper proposes a new SLAM (Simultaneous Localization and Mapping) algorithm based on hybrid map method. We express the environment surrounding mobile robot with a grid and a feature map. Using the reliability of estimation for individual map, we calculate the importance factor for Rao-Blackwellized Particle Filter (RBPF) resampling. In this way, we improve the accuracy of the algorithm and reduce computational complexity. Experimental results verify the feasibility and effectiveness of our algorithm.

关键词

Particle filterSimultaneous localization and mappingResamplingComputer scienceAlgorithmFeature (linguistics)Reliability (semiconductor)Artificial intelligenceMobile robotHybrid algorithm (constraint satisfaction)

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