Simultaneous localization and mapping (SLAM) is a fundamental task for numerous
applications such as autonomous navigation and exploration. Despite many SLAM datasets …

Robustness is a crucial factor for the successful deployment of robots in unstructured
environments, particularly in the domain of Simultaneous Localization and Mapping (SLAM) …

Visual simultaneous localization and mapping (V-SLAM) plays a crucial role in the field of
robotic systems, especially for interactive and collaborative mobile robots. The growing …

We present improvements to Kimera, an open-source metric-semantic visual-inertial SLAM
library. In particular, we enhance Kimera-VIO, the visual-inertial odometry pipeline powering …

This paper presents an approach to implem enting centralized multirobot simultaneous
localization and mapping (MR-SLAM) in an unknown environment based on LiDAR sensors …

The important manifestation of robot intelligence is the ability to naturally interact and
autonomously make decisions. Traditional approaches to robot control often …

In the realm of robotics, the quest for achieving real-world autonomy, capable of executing
large-scale and long-term operations, has positioned place recognition (PR) as a …

In this paper, we propose a dynamic object elimination algorithm that combines semantic
and geometric constraints to address the problem of visual SLAM being easily affected by …

In the past decade, although single-robot perception has made significant advancements,
the exploration of multi-robot collaborative perception remains largely unexplored. This …

This paper introduces a novel incremental distributed back-end algorithm for Collaborative
Simultaneous Localization and Mapping (C-SLAM). For real-world deployments, robotic …