Multi Camera IMU

Multi-camera IMU systems integrate data from multiple inertial measurement units (IMUs) and cameras for robust and accurate state estimation, primarily focusing on improving localization and motion tracking in challenging environments. Current research emphasizes developing efficient and robust algorithms, such as extended Kalman filters and Gaussian processes, to handle asynchronous sensor data, perform online calibration of both intrinsic and extrinsic parameters, and fuse data from diverse sensor types (e.g., LiDAR). These advancements are significantly impacting robotics, autonomous vehicles, and other applications requiring precise and reliable pose estimation, particularly in GPS-denied or dynamically changing environments.