자율 객체 추종을 위한 파티클 필터 기반 위치 추정 및 제어 시스템

Abstract

Tracking objects in large indoor spaces like airports poses various challenges due to dynamic obstacles such as crowds. This paper presents a particle filter-based system that integrates camera and Ultra-Wideband sensor data for estimating and controlling object position. The camera provides detailed visual detection, while Ultra-Wideband ensures robust positioning under occlusion. By fusing these inputs, the system achieves accurate object tracking in crowded settings. A control algorithm utilizes the estimated position to enable smooth and precise object following. Experiments in an airport-like environment validate the system’s effectiveness, demonstrating reliable performance in dynamic conditions. This work contributes to the field of autonomous navigation in complex indoor spaces.