Active simultaneous localization and mapping (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …

Autonomous exploration of unknown environments using a team of mobile robots demands
distributed perception and planning strategies to enable efficient and scalable performance …

This paper proposes a method for learning continuous control policies for exploration and
active landmark localization. We consider a mobile robot detecting landmarks within a …

The problem of active mapping aims to plan an informative sequence of sensing views given
a limited budget such as distance traveled. This paper considers active occupancy grid …

This paper proposes a novel\emph {model-based policy gradient algorithm} for tracking
dynamic targets using a mobile robot, equipped with an onboard sensor with a limited field …

This paper proposes a novel active Simultaneous Localization and Mapping (SLAM) method
with continuous trajectory optimization over a stochastic robot dynamics model. The problem …

This paper proposes an optimal active perception strategy using the Constructibility Gramian
(CG) as a metric to quantify the richness of the information acquired along the planned …

In this paper, we present a novel algorithm for the 3-D active multi-robot multi-target tracking
problem in a distributed manner. For a team of robots equipped with sensors, we design the …

In this paper, we propose a comprehensive solution for 3-D active target tracking with
multiple robots in a fully distributed setting. Here multiple robots cooperatively estimate their …

This work presents and evaluates a novel strategy for robotic exploration that leverages
human models of uncertainty perception. To do this, we introduce a measure of uncertainty …