The use of aerial swarms to solve real-world problems has been increasing steadily,
accompanied by falling prices and improving performance of communication, sensing, and …

Abstract Purpose of Review This review summarizes the broad roles that communication
formats and technologies have played in enabling multi-robot systems. We approach this …

Developing a safe and efficient collision-avoidance policy for multiple robots is challenging
in the decentralized scenarios where each robot generates its paths with limited observation …

Multi-agent pathfinding (MAPF) is an area of expanding research interest. At the core of this
research area, numerous diverse search-based techniques were developed in the past 6 …

Abstract Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem that asks
us to plan collision-free paths for a team of cooperative agents. In this work, we show that …

We consider the problem of routing a large fleet of drones to deliver packages
simultaneously across broad urban areas. Besides flying directly, drones can use public …

This letter introduces a hybrid algorithm of deep reinforcement learning (RL) and Force-
based motion planning (FMP) to solve distributed motion planning problem in dense and …

Recent years have shown a large increase in applications and research of problems that
include moving a fleet of physical robots. One particular application that is currently a multi …

Abstract Multi-Agent Path Finding (MAPF) is well studied in both AI and robotics. Given a
discretized environment and agents with assigned start and goal locations, MAPF solvers …

This paper introduces recently developed Aquila Optimization Algorithm specifically
configured for Multi-Robot space exploration. The proposed hybrid framework “Coordinated …