Sensors, Vol. 18, Pages 3168: Self-Diagnosis of Localization Status for Autonomous Mobile Robots
In this study, two indicators are empirically defined for the self-diagnosis of localization status. Each indicator shows significant changes when there are difficulties in light detection and ranging (LiDAR) sensor-based localization. In addition, the classification model of localization status is trained through machine learning using the two indicators. A robot can diagnose the localization status itself using the proposed classification model. To verify the usefulness of the proposed method, we carried out localization experiments in real environments. The proposed classification model successfully detected situations where the localization accuracy is significantly degraded due to extreme environmental changes.
Source: Sensors - Category: Biotechnology Authors: Jiwoong Kim Jooyoung Park Woojin Chung Tags: Article Source Type: research
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