Robot localization and mapping algorithms are essential for enabling autonomous robots to operate in complex and dynamic environments, such as military operations. These algorithms allow robots to ...

Despite the massive progress in multi-robot localization, mapping, and planning in recent years, many challenges remain. Similar to single robot systems, the issues of long-term operations, robustness ...

Abstract: Simultaneous Localization and Mapping (SLAM) means to estimate the positions and orientations of the mobile robot and to construct the model ... implement and validate graph-based robust ...

By using ROS and Gazebo, you can document your robot's navigation and localization by recording and playing back data, visualizing sensor readings and maps, and generating reports and graphs.

2016 IROS Achievement of localization ... motion tracking of a legged robot using adaptive time surface---demo 2022 ICRA R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled ...

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Artificial intelligence (AI) techniques like deep learning (DL) are contributing significantly to advancements in robot localization and mapping (RLAM). By analyzing data from various sensors like ...

Abstract: We describe a localization and map building approach for a mobile robot which employs an annotated generalized Voronoi graph as its representation of the environment. The core of our ...

Robot localization and mapping are fundamental capabilities for mobile robots operating in the real world. Even more challenging than these individual problems is their combination: simultaneous ...

Robot localization and mapping are fundamental capabilities for mobile robots operating in the real world. Even more challenging than these individual problems is their combination: simultaneous ...