Collaborative SLAM enables a group of agents to simultaneously co-localize and jointly map
an environment, thus paving the way to wide-ranging applications of multi-robot perception …

Although cooperative localization (CL) is fundamental to multirobot systems, current
algorithms suffer from the tracking of interdependencies, information fusion from multiple …

Mobile robotics applications process large amounts of data in real-time and require compute
platforms that provide high performance and energy-efficiency. FPGAs are well-suited for …

In this paper we present a consistent and distributed state estimator for multi-robot
cooperative localization (CL) which efficiently fuses environmental features and loop-closure …

Now that drones have evolved from bulky platforms to agile devices, a challenge is to
combine multiple drones into an integrated autonomous system, offering functionality that …

With the advancements of communication technologies and the Global Navigation Satellite
Systems (GNSS), research and development in GNSS-based Cooperative Positioning (CP) …

This paper presents a novel approach to recover outdated cross-covariance between
correlated agents at the moment they perform joint observations. This allows to render …

Fusing information from multiple sensors in aprobabilistic framework can significantly
improve the estimation of the system's states, allow for redundancy, and for adaptations in …

The localization and mapping of the robotics team in unknown environments, especially
GNSS denied environments, is a prerequisite for the perception and exploration of unknown …

This paper addresses the problem of decentralized, collaborative state estimation in robotic
teams. In particular, this paper considers problems where individual robots estimate similar …