Robust Monte Carlo localization based on vector model

Bing Gang Jhong, Mei Yung Chen

研究成果: 書貢獻/報告類型會議貢獻

摘要

This paper proposed an enhanced Monte Carlo localization algorithm, which is more effective, stable and robust than traditional localization algorithm by using many strengthening mechanisms, such as vector model, re-initialization and reverse convergence. The vector model redefines the pattern of environment map, so that the localization result is not limited by the resolution of map. Re-initialization gives second chance when the algorithm is missing the right location and can't jump out the local solution. Reverse convergence, the most important in this paper, can let the algorithm spread particle swarm moderately. It is simple but very useful, especially for the case within noise or sensing distance limitations in the sensors. The simulation results also show the excellent performance of proposed algorithm.

原文英語
主出版物標題2016 IEEE International Conference on System Science and Engineering, ICSSE 2016
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781467389662
DOIs
出版狀態已發佈 - 2016 八月 24
事件2016 IEEE International Conference on System Science and Engineering, ICSSE 2016 - Puli, 臺灣
持續時間: 2016 七月 72016 七月 9

出版系列

名字2016 IEEE International Conference on System Science and Engineering, ICSSE 2016

其他

其他2016 IEEE International Conference on System Science and Engineering, ICSSE 2016
國家臺灣
城市Puli
期間2016/07/072016/07/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence
  • Control and Optimization
  • Control and Systems Engineering

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