Improvement of Localization Algorithm for Indoor and Outdoor Navigation of Autonomous Robots

초록

Location estimation for waypoint-based autonomous driving robots primarily relies on SLAM (Simultaneous Localization and Mapping) and GNSS (Global Navigation Satellite System) technologies. GNSS performs well in open areas but struggles with signal issues, while SLAM offers high accuracy in feature-rich environments but faces challenges in open spaces. This study integrates SLAM and GNSS, enabling seamless switching between systems when one encounters difficulties. The combined system ensures consistency by aligning coordinate systems and directional data. Experiments in indoor, forest, and open environments demonstrate that the switching algorithm enables stable autonomous driving in diverse conditions, effectively leveraging the strengths of both systems. © ICROS 2025.

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