Simultaneous Localization and Mapping (SLAM) is a critical technology for modern mobile robotics. Robots with sensors like monocular, binocular, RGB-D cameras, and LIDAR can build maps of unknown ...

Simultaneous Localization and Mapping (SLAM) uses observations to construct a graph, which often contains both environments (mapping), and robot trajectories (localization). RoCAL focuses on building ...

This article explores how deep learning (DL) techniques are transforming robot localization and mapping (RLAM) by leveraging data from various sensors like cameras and LiDAR. DL-based approaches ...

The Simultaneous Localization And Mapping (SLAM) Technology market is segmented based on By Type, By Application and Geography, offering a comprehensive analysis of the industry.

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, and Abhinav Valada.

In this paper, a simultaneous localization and mapping algorithm based on the weighted asynchronous fusion of laser and vision sensors is proposed for an assistant robot. When compared to the ...