The context is sensor control for multi-object Bayes filtering in the framework of partially
observed Markov decision processes (POMDPs). The current information state is …

Active Position Estimation (APE) is the task of localizing one or more targets using one or
more sensing platforms. APE is a key task for search and rescue missions, wildlife …

Abstract Planning in Partially Observable Markov Decision Processes (POMDPs) inherently
gathers the information necessary to act optimally under uncertainties. The framework can …

With the recent advent of risk awareness, decision-making algorithms' complexity increases,
posing a severe difficulty to solve such formulations of the problem online. Our approach is …

A sensor management scheme that focuses on managing the uncertainty in the threat level
of targets is proposed. The scheme selects the best sensing mode such that the uncertainty …

The recursive procedure to compute the posterior Cramér-Rao lower bound (PCRLB) for
sequential Bayesian estimators, derived by Tichavsky, provides an off-line performance …

This paper mainly studies the localization and mapping of range sensing robots in the
confidence-rich map (CRM) and then extends it to provide a full state estimate for …

In this paper, we consider online planning in par-tially observable domains. Solving the
corresponding POMDP problem is a very challenging task, particularly in an online setting …

As an emerging topic, the swarm of autonomous unmanned aerial vehicles (UAVs) has
been attracting great attention. Due to the indeterminacy of sensors, distributed cooperative …

In sensor management, the usefulness of information theoretic measures seems to be
validated by a large number of empirical studies, but theoretical justification presented until …