Robustness is key to engineering, automation, and science as a whole. However, the
property of robustness is often underpinned by costly requirements such as over …

Multi-robot simultaneous localization and mapping (SLAM) is a crucial capability to obtain
timely situational awareness over large areas. Real-world applications demand multi-robot …

Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

To achieve collaborative tasks, robots in a team need to have a shared understanding of the
environment and their location within it. Distributed Simultaneous Localization and Mapping …

Decentralized visual simultaneous localization and mapping (SLAM) is a powerful tool for
multi-robot applications in environments where absolute positioning is not available. Being …

We present the first fully distributed multi-robot system for dense metric-semantic
Simultaneous Localization and Mapping (SLAM). Our system, dubbed Kimera-Multi, is …

Motivated by the tremendous progress we witnessed in recent years, this paper presents a
survey of the scientific literature on the topic of Collaborative Simultaneous Localization and …

In this paper, we present a Covariance Intersection (CI)-based algorithm for reducing the
processing and communication complexity of multi-robot Cooperative Localization (CL) …

This paper presents an consistent decentralized data fusion approach for robust multi-robot
SLAM in dangerous, unknown environments. The DDF-SAM 2.0 approach extends our …

We consider the following problem: a team of robots is deployed in an unknown
environment and it has to collaboratively build a map of the area without a reliable …