Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Recent years are seeing an increasing need for on-line monitoring of deployed distributed teams of cooperating agents, e.g., for visualization, or performance tracking. However, i...
We present an overview of FAB-MAP, an algorithm for place recognition and mapping developed for infrastructure-free mobile robot navigation in large environments. The system allow...
The impact of process variation in state of the art technology makes traditional (worst case) designs unnecessarily pessimistic, which translates to suboptimal designs in terms of...
Real-world data -- especially when generated by distributed measurement infrastructures such as sensor networks -- tends to be incomplete, imprecise, and erroneous, making it impo...