Localization Handover for Mobile Robots: A Seamless Indoor-Outdoor Approach

Abstract This paper presents a seamless indoor-outdoor localization approach for autonomous mobile robots by integrating multiple technologies: Ultra-Wideband (UWB) for high-precision indoor positioning, Global Positioning System (GPS) for outdoor global navigation, odometry for detailed granularity, and an Inertial Measurement Unit (IMU) for responsive motion tracking. The method employs loosely coupled Extended Kalman Filters (EKFs) to fuse these data sources, dynamically adjusting based on signal quality to ensure continuous and reliable localization in transition areas. Through extensive validation in simulation environments, the proposed system demonstrates the ability to mitigate the challenges posed by incomplete localization coverage in indoor-outdoor transition zones. The results show significant improvement in localization accuracy, enabling safer and more efficient robot navigation across diverse environments. Quantitative comparisons with recent studies demonstrate that our method achieves localization performance similar to tightly-coupled approaches, yet with significantly lower computational complexity, simpler implementation, greater flexibility in sensor integration, and enhanced robustness to individual sensor failures.