Pedestrian Localization

Pedestrian localization aims to accurately determine the position of pedestrians, a crucial task with applications in autonomous driving and smart city infrastructure. Current research focuses on robust sensor fusion techniques, often combining inertial measurement units (IMUs) with visual data (cameras) or wireless signals (UWB, BLE, WiFi), employing methods like graph optimization and generative adversarial networks (GANs) to improve accuracy and handle data inconsistencies. These advancements address challenges like sensor drift and occlusions, leading to more reliable localization even in challenging environments, ultimately enhancing safety and efficiency in various applications.