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Hierarchical-map Updating Approach for Simultaneous Localization and Mapping of Mobile Robots

Journal from gdlhub / 2016-11-09 10:14:05
Oleh : Yingmin Yi, Zhimin Wang, Telkomnika
Dibuat : 2015-03-01, dengan 1 file

Keyword : hierarchical-map updating, computational complexity, simultaneous localization and map building, mobile robots
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/1275

For the tremendously increasing of system state in wild field, the computational complexities of mobile robot system should be taken into account. This paper proposes a hierarchical-map updating approach for simultaneous localization and mapping of robots. The basic idea of hierarchical-map is defining two kinds of maps during the recursive updating process, namely local map (upper map) and global map (lower map). The system states will be updated by the preset maps. The hierarchical-map updating process is just for the upper map and the lower map is updated after a certain running term. In the calculation, the state data of the upper map is far less than that of the lower map. It is validated by the experiments that, the approach is more optimal than others in computational complexities while ensuring the consistency estimate.

Deskripsi Alternatif :

For the tremendously increasing of system state in wild field, the computational complexities of mobile robot system should be taken into account. This paper proposes a hierarchical-map updating approach for simultaneous localization and mapping of robots. The basic idea of hierarchical-map is defining two kinds of maps during the recursive updating process, namely local map (upper map) and global map (lower map). The system states will be updated by the preset maps. The hierarchical-map updating process is just for the upper map and the lower map is updated after a certain running term. In the calculation, the state data of the upper map is far less than that of the lower map. It is validated by the experiments that, the approach is more optimal than others in computational complexities while ensuring the consistency estimate.

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