Improving RGB-D SLAM in dynamic environments using semantic aided segmentation
Abstract
Summary Most conventional simultaneous localization and mapping (SLAM) approaches assume the working environment to be static. In a highly dynamic environment, this assumption divulges the impediments of a SLAM algorithm that lack modules that distinctively attend to dynamic objects despite the inclusion of optimization techniques. This work exploits such environments and reduces the effects of dynamic objects in a SLAM algorithm by separating...
Paper Details
Title
Improving RGB-D SLAM in dynamic environments using semantic aided segmentation
Published Date
Nov 16, 2021
Journal
Volume
40
Issue
6
Pages
2065 - 2090
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Notes
History