Decision making under uncertainty is at the heart of any autonomous syst...
Autonomous agents that operate in the real world must often deal with pa...
Simultaneous localization and mapping (SLAM) are essential in numerous
r...
Online decision making under uncertainty in partially observable domains...
Real-world problems often require reasoning about hybrid beliefs, over b...
One of the most complex tasks of decision making and planning is to gath...
Risk awareness is fundamental to an online operating agent. However, it
...
Semantic simultaneous localization and mapping is a subject of increasin...
Autonomous agents operating in perceptually aliased environments should
...
Active Simultaneous Localization and Mapping (SLAM) is the problem of
pl...
Unresolved data association in ambiguous and perceptually aliased
enviro...
Reasoning about uncertainty is vital in many real-life autonomous system...
In this work, we examine the problem of online decision making under
unc...
Partially Observable Markov Decision Processes (POMDPs) are notoriously ...
We investigate the problem of autonomous object classification and seman...
It is a long-standing objective to ease the computation burden incurred ...
In this paper, we consider online planning in partially observable domai...
Deciding what's next? is a fundamental problem in robotics and Artificia...
We present an approach for multi-robot consistent distributed localizati...
Expressiveness of deep models was recently addressed via the connection
...
In this work, we introduce a new approach for the efficient solution of
...
Inference and decision making under uncertainty are key processes in eve...
Fast covariance calculation is required both for SLAM (e.g. in order to ...
In this paper we contribute a novel algorithm family, which generalizes ...
Determining a globally optimal solution of belief space planning (BSP) i...
A probability density function (pdf) encodes the entire stochastic knowl...
We develop a belief space planning (BSP) approach that advances the stat...