This paper addresses the problem of controlling mobile sensing systems to improve the
accuracy and efficiency of gathering information autonomously. It applies to scenarios such …

This letter considers the problem of reducing uncertainty about a physical process of interest
by designing sensing trajectories for a team of robots. This active information gathering …

This paper addresses the Multi-Robot Active In-formation Acquisition (AIA) problem, where a
team of mobile robots, communicating through an underlying graph, estimates a hidden …

This paper proposes a novel highly scalable sampling-based planning algorithm for multi-
robot active information acquisition tasks in complex environments. Active information …

Autonomous robot networks are an effective tool for monitoring large-scale environmental
fields. This paper proposes distributed control strategies for localizing the source of a noisy …

This paper considers situations in which a team of mobile sensor platforms autonomously
explores an environment to detect and localize an unknown number of targets. Individual …

This paper proposes a novel highly scalable sampling-based planning algorithm for multi-
robot active information acquisition tasks in complex environments. Active information …

This paper presents a distributed control algorithm to drive a group of robots to spread out
over an environment and provide adaptive sensor coverage of that environment. The robots …

We address the persistent monitoring problem in two-dimensional mission spaces where the
objective is to control the trajectories of multiple cooperating agents to minimize an …

We introduce the use of hierarchical clustering for relaxed deterministic coordination and
control of multiple robots. Traditionally, an unsupervised learning method, hierarchical …