This work addresses the problem of efficient online exploration and map** using multi-
robot teams via a new distributed algorithm for multi-robot exploration, distributed sequential …

The problem of decentralized multi-robot target tracking asks for jointly selecting actions, eg,
motion primitives, for the robots to maximize target tracking performance with local …

In this article, we design algorithms to protect swarm-robotics applications against sensor
denial-of-service attacks on robots. We focus on applications requiring the robots to jointly …

The maximization of submodular functions is an NP-Hard problem for certain subclasses of
functions, for which a simple greedy algorithm has been shown to guarantee a solution …

This article presents a data-driven method for computing reachable sets where active
learning (AL) is used to reduce the computational burden. Set-based methods used to …

Many problems that are relevant to sensor networks such as active sensing and coverage
planning have objectives that exhibit diminishing returns and specifically are submodular …

We study the problem of tracking multiple moving targets using a team of mobile robots.
Each robot has a set of motion primitives to choose from in order to collectively maximize the …

Multi-robot decision-making is the process where multiple robots coordinate actions. In this
paper, we aim for efficient and effective multi-robot decision-making despite the robots' …

Decentralized policies for information gathering are required when multiple autonomous
agents are deployed to collect data about a phenomenon of interest when constant …

Joint utility-maximization problems for multi-agent systems often should be addressed by
distributed strategy-selection formulation. Constrained by discrete feasible strategy sets …