Pose Graph

A pose graph represents the spatial relationships between different viewpoints or poses, typically used in robotics and computer vision for tasks like Simultaneous Localization and Mapping (SLAM). Current research focuses on improving pose graph construction and optimization, employing techniques like graph neural networks, normalizing flows, and hierarchical approaches to handle noise, outliers, and scale ambiguities, particularly in challenging scenarios with sparse data or limited field-of-view. These advancements enhance the robustness and efficiency of SLAM systems, enabling more accurate 3D environment reconstruction and improved robot navigation, object recognition, and human motion capture. The resulting improvements have significant implications for autonomous systems, augmented/virtual reality, and other applications requiring accurate spatial understanding.