Vision Based Localization

Vision-based localization aims to determine a system's location and orientation using only visual data, primarily addressing the challenge of autonomous navigation in GPS-denied or challenging environments. Current research focuses on improving accuracy and robustness through techniques like visual simultaneous localization and mapping (SLAM), often incorporating deep learning for feature extraction and pose estimation, and exploring alternative sensor modalities (e.g., event cameras) to enhance performance in low-light or dynamic conditions. This field is crucial for advancing autonomous vehicles, robotics, and assistive technologies, offering cost-effective and infrastructure-independent solutions for precise localization in diverse settings.