8.6k citations
- University of HelsinkiFI101 papers
- Centre National de la Recherche ScientifiqueFR89 papers
- California Institute of TechnologyUS67 papers
- Université de StrasbourgFR66 papers
- Charles UniversityCZ65 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di PadovaIT65 papers
- University of TurinIT65 papers
- Eötvös Loránd UniversityHU64 papers
- Helsinki Institute of PhysicsFI64 papers
- Rutherford Appleton LaboratoryGB63 papers
- University of PaduaIT63 papers
- Carnegie Mellon UniversityUS62 papers
30 papers · 1 filter
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…
An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments
Ali Agha, Kyohei Otsu, Benjamin Morrell +86
This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Sub…
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…
Combined Aerial Cooperative Tethered Carrying and Path Planning for Quadrotors in Confined Environments
Marios-Nektarios Stamatopoulos, Panagiotis Koustoumpardis, Achilleas Santi Seisa +1
In this article, a novel combined aerial cooperative tethered carrying and path planning framework is introduced with a special focus on applications in confined environments. The…
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…