Three-dimensional point cloud classification is fundamental but still challenging in 3-D
vision. Existing graph-based deep learning methods fail to learn both low-level extrinsic and …

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for
autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved …

Abstract Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. Over the last two decades …

Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. In the last two decades, LiDAR …

The research groups in computer vision, graphics, and machine learning have dedicated a
substantial amount of attention to the areas of 3D object reconstruction, augmentation, and …

Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …

Robust and accurate localization is a basic requirement for mobile autonomous systems.
Pole-like objects, such as traffic signs, poles, and lamps are frequently used landmarks for …

LiDAR mapping is important yet challenging in self-driving and mobile robotics. To tackle
such a global point cloud registration problem, DeepMapping converts the complex map …

Abstract Building Information Modeling (BIM) has increasingly been adopted as an as-
planned construction state to provide essential support for fine construction. However, some …

Artificial Intelligence-based systems are required to interact with dynamic environments to
continuously learn, retain and effectively utilize knowledge. Present AI-based systems …