Object-level data association and pose estimation play a fundamental role in semantic
SLAM, which remain unsolved due to the lack of robust and accurate algorithms. In this …

Object SLAM is considered increasingly significant for robot high-level perception and
decision-making. Existing studies fall short in terms of data association, object …

Multi-robot mapping and environment modeling have several advantages that make it an
attractive alternative to the mapping with a single robot: faster exploration, higher fault …

In this article, we propose a visual simultaneous localization and mapping (SLAM) method
by predicting and updating line flows that represent sequential 2-D projections of 3-D line …

Vision-based localization is a cost-effective and, thus, attractive solution for many intelligent
mobile platforms. However, its accuracy and especially robustness still suffer from low …

In semantic visual simultaneous localization and mapping (SLAM), accurate object-level
reconstruction of the environment based on the deep learning techniques is very crucial for …

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness
changes rather than integrating absolute image intensities. Owing to this design, the sensor …

In applications, such as scene reconstruction and odometry, accurate matching associations
for 3-D lines are crucial. Real-world scenes introduce inconsistencies due to variations in …

This research develops an accurate and efficient method for the Perspective-n-Line (PnL)
problem. The developed method addresses and solves PnL via exploiting the problem's …

Monocular visual-inertial tracking without good initialization easily fails due to its non-linear
nature. Rapid and accurate metric initialization is crucial. In this paper, we propose a novel …