Simultaneous localization and mapping or structure-from-motion is an important subfield in computer vision and robotics. It enables the 3D reconstruction of unknown environments from moving cameras and allows for localizing in the built map. We investigate direct visual SLAM approaches that enable robots to acquire 3D maps of the environment and localize in the maps in real-time. In prior works, we have studied SLAM with RGB-D cameras~(e.g.,~[ ]) in indoor environments, and monocular~[ ], stereo (e.g.,~[ ]) and stereo-inertial cameras~[ ] in outdoor environments. In the period 2022-2024, we have developed visual-inertial state-estimation methods for localizing a quadruped robot~[ ] and wheeled robots~[ ] while incorporating kinematic and dynamic models that further regularize perception.
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