The use of aerial swarms to solve real-world problems has been increasing steadily,
accompanied by falling prices and improving performance of communication, sensing, and …

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 …

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 …

Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, and complex
subterranean environments is a challenging problem. Sensors must operate in off-nominal …

Robotic collaboration promises increased robustness and efficiency of missions with great
potential in applications, such as search‐and‐rescue and agriculture. Multiagent …

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

Decentralized state estimation is one of the most fundamental components of autonomous
aerial swarm systems in GPS-denied areas; yet, it remains a highly challenging research …

Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital component for
successful multi-robot operations in environments without an external positioning system …

We present a multi-robot system for GPS-denied search and rescue under the forest canopy.
Forests are particularly challenging environments for collaborative exploration and mapping …