Vision Aided Inertial Navigation

Vision-aided inertial navigation (VINS) integrates data from inertial measurement units (IMUs) and cameras to estimate a vehicle's pose (position and orientation), particularly in GPS-denied environments. Current research emphasizes improving the accuracy and efficiency of VINS algorithms, focusing on novel filter designs like invariant extended Kalman filters and square root information filters, often incorporating advanced techniques such as preconditioning to enhance numerical stability. These advancements are crucial for applications such as autonomous navigation in robotics and unmanned aerial vehicles (UAVs), enabling robust and reliable localization in challenging conditions.