most citedMulti-Agent Path Finding Using Conflict-Based Search and Structural-Semantic Topometric Maps

1 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO20251 cited

Multi-Agent Path Finding Using Conflict-Based Search and Structural-Semantic Topometric Maps

Scott Fredriksson, Yifan Bai, Akshit Saradagi +1

As industries increasingly adopt large robotic fleets, there is a pressing need for computationally efficient, practical, and optimal conflict-free path planning for multiple robot…

cs.RO2025

Deployment of an Aerial Multi-agent System for Automated Task Execution in Large-scale Underground Mining Environments

Niklas Dahlquist, Samuel Nordström, Nikolaos Stathoulopoulos +3

In this article, we present a framework for deploying an aerial multi-agent system in large-scale subterranean environments with minimal infrastructure for supporting multi-agent o…

cs.RO2024

Investigating the Impact of Communication-Induced Action Space on Exploration of Unknown Environments with Decentralized Multi-Agent Reinforcement Learning

Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1

This paper introduces a novel enhancement to the Decentralized Multi-Agent Reinforcement Learning (D-MARL) exploration by proposing communication-induced action space to improve th…

cs.RO20241 cited

Reinforcement Learning Driven Multi-Robot Exploration via Explicit Communication and Density-Based Frontier Search

Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1

Collaborative multi-agent exploration of unknown environments is crucial for search and rescue operations. Effective real-world deployment must address challenges such as limited i…