1 citations · 1 across the 5 of their papers we have counts for
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Safe Heterogeneous Multi-Agent RL with Communication Regularization for Coordinated Target Acquisition
Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1
This paper introduces a decentralized multi-agent reinforcement learning framework enabling structurally heterogeneous teams of agents to jointly discover and acquire randomly loca…
Platform-Agnostic Reinforcement Learning Framework for Safe Exploration of Cluttered Environments with Graph Attention
Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1
Autonomous exploration of obstacle-rich spaces requires strategies that ensure efficiency while guaranteeing safety against collisions with obstacles. This paper investigates a nov…
A Graph-Based Reinforcement Learning Approach with Frontier Potential Based Reward for Safe Cluttered Environment Exploration
Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1
Autonomous exploration of cluttered environments requires efficient exploration strategies that guarantee safety against potential collisions with unknown random obstacles. This pa…
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…
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…