Abstract Purpose of Review Current real-world interaction between humans and robots is
extremely limited. We present challenges that, if addressed, will enable humans and robots …

In recent years, teams of robot and Unmanned Aerial Vehicles (UAVs) have been
commissioned by researchers to enable accurate, online wildfire coverage and tracking …

In the context of heterogeneous multirobot teams deployed for executing multiple tasks, this
article develops an energy-aware framework for allocating tasks to robots in an online …

Deep neural networks (DNNs) have shown remarkable performance in a variety of domains
such as computer vision, speech recognition, and natural language processing. Recently …

High-performing teams learn intelligent and efficient communication and coordination
strategies to maximize their joint utility. These teams implicitly understand the different roles …

Effective deployment of multi-robot teams requires solving several interdependent problems
at varying levels of abstraction. Specifically, heterogeneous multi-robot systems must …

This letter presents a resilient mechanism to allocate heterogeneous robots to tasks under
difficult environmental conditions such as weather events or adversarial attacks. Our primary …

This article is concerned with the multitask multiagent allocation problem via many-objective
optimization for multiagent systems (MASs). First, a novel layered MAS model is constructed …

We propose a collaborative planning and control algorithm to enhance cooperation for
composite teams of autonomous robots in dynamic environments. Composite robot teams …

Multi agent strategies in mixed cooperative-competitive environments can be hard to craft by
hand because each agent needs to coordinate with its teammates while competing with its …