Market-based methods have received significant attention for solving the multi-robot task
allocation problem. They have been used in a variety of multi-robot scenarios, such as …

Purpose This paper aims to present a concise review on the variant state-of-the-art dynamic
task allocation strategies. It presents a thorough discussion about the existing dynamic task …

To address the problem of multirobot collaborative task scheduling considering the
degradation of industrial robot performance and the recovery of robot performance through …

This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate
building smart warehouses to achieve the promising vision of industry 4.0. We focus on four …

In this paper, we propose an iterative strategy to enhance the performance of task
assignment and path planning in applications of distributed multiple unmanned aerial …

Abstract Purpose of Review Robotic patrolling aims at protecting a physical environment by
deploying a team of one or more autonomous mobile robots in it. A key problem in this …

In this paper, we apply deep reinforcement learning (DRL) to solve the flocking control
problem of multi-robot systems in complex environments with dynamic obstacles. Starting …

Aiming at the problem of UAV swarms with distributed subsets performing cooperative
reconnaissance-and-attack tasks on multi-targets in complex and uncertain combat …

The auction algorithm is a widely used method for task assignments. However, most existing
auction algorithms yield poor performance when applied to multi-UAVs dynamic task …

To enhance the mission success rate, the multi-agent system (MAS) often adopts a formation
form to shuttle over complex terrain. Compared with obstacle avoidance in other multi-agent …