3D Localization

3D localization focuses on accurately determining the three-dimensional position of objects or agents within a scene, a crucial task across diverse fields. Current research emphasizes robust methods for fusing data from multiple sensor modalities (e.g., RGB, LiDAR, ultrasound, mmWave radar) and employing advanced algorithms like neural networks (including CNNs and MLPs), Kalman filtering, and Monte Carlo localization to improve accuracy and handle challenging environments (e.g., GPS-denied, cluttered, dynamic). These advancements have significant implications for applications ranging from autonomous driving and robotics to medical imaging and augmented reality, enabling safer and more efficient systems.