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Edwin Meriaux

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Publications

Dungeon and Visibility World Generator
Edwin Meriaux
Antonio Loría
Gregory Dudek
Robotic exploration, coverage, and multi-agent deployment algorithms require reproducible environments with controllable geometry and visibi… (voir plus)lity. This paper presents the Dungeon and Visibility World Generator, an open-source framework for constructing two- and three-dimensional environments and evaluating geometric line-of-sight. The framework supports orthogonal, polygonal or polyhedral, and curvilinear geometries, with six construction families covering scattered rooms, clusters, winding passages, caverns, branches, and loops. Room dimensions, passage structures, obstacles, and spatial placement can be controlled through configurable parameters and probability distributions. Each generated environment provides continuous free-space geometry and a corresponding discrete occupancy representation. A Rust-based visibility engine supports line-of-sight queries in both representations, enabling the evaluation of observable regions from arbitrary agent positions. The framework records configurations, generated geometries, occupancy grids, and visibility results to support reproducible experiments. We demonstrate the generator across all six geometry classes, examine how geometry and spatial resolution affect visibility, and evaluate generation time and reproducibility. The resulting framework provides a configurable foundation for evaluating robotic exploration, coverage, and multi-agent deployment algorithms in diverse environments.
2026-10-13
arXiv (prépublication)
doi.org
arxiv.org
CollisionGAT: Controller-Agnostic One-Step Collision Screening for Multi-Agent Motion
Alan Debbas
Edwin Meriaux
Gregory Dudek
Before a team of robots moves, each proposed step must be checked for collisions with other robots and with obstacles. We present CollisionG… (voir plus)AT, a graph-attention network that reads the current and proposed states of moving agents together with locally relevant stationary obstacles and returns one collision-risk score per moving agent. Any controller can use these scores to accept, repair, replan, or postpone a proposed step. We mount CollisionGAT on a continuous path-following controller and on GATeD, an obstacle-blind D* Lite planner that uses typed vetoes to update its planning graphs. Exact geometric checks supply the training labels and independently audit every executed step.
2026-09-25
arXiv (prépublication)
doi.org
arxiv.org
On the Control of Mobile Ad-Hoc Agent Deployments in Partially Observed Space
Edwin Meriaux
Louis-Roy Langevin
Shuo Wen
Ndiamé Ndiaye
Gregory Dudek
Antonio Loría
We study the online deployment of mobile ad hoc networks in unknown orthogonal environments, formalized as the Partially Observable Cooperat… (voir plus)ive Guard Art Gallery Problem. We give a full proof that CADENCE algorithms achieve full coverage while maintaining a connected visibility graph using at most
2026-09-18
arXiv (prépublication)
doi.org
arxiv.org
Do LLMs Beat Nash? Testing Decentralized Coordination in Self-Play Multi-Agent Games
Deborah Sinishaw
Qile Zhu
Edwin Meriaux
Gregory Dudek
Large language model agents deployed without a central controller are often assumed to require communication to coordinate their actions. We… (voir plus) ask what remains possible without it: when independent instances of the same model cannot communicate, can they still reason about their counterparts well enough to exceed the standard game-theoretic baseline for uncoordinated play? We introduce a benchmark of one-shot, no-communication games in which each of thirteen language models is told only that its counterparts are running the same model and is evaluated against the Nash equilibrium of the underlying game. In two-player matrix games spanning seven archetypes and two to ten actions per player, two frontier-hosted models consistently exceed their Nash benchmark, approaching the optimal joint outcome in several archetypes, while most open-weight models achieve only partial gains that vary sharply by game structure. Performance degrades substantially in team-based games with four or more interchangeable agents, particularly as the action space grows, suggesting that whatever capability drives self-play gains in dyadic games does not transfer to larger multi-agent teams.
2026-08-11
arXiv (prépublication)
doi.org
arxiv.org
AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping
Edwin Meriaux
Shuo Wen
David Widhalm
Zhizun Wang
Junming Shi
Mariana Sosa Guzmán
Kalvik Jakkala
Bennett Carley
Elias Sokolova
Yogesh Girdhar
Monika Roznere
Jason O’Kane
Junaed Sattar
Gregory Dudek
Marine environments present significant challenges for perception and autonomy due to dynamic surfaces, limited visibility, and complex inte… (voir plus)ractions between aerial, surface, and submerged sensing modalities. This paper introduces the Aerial Marine Perception Dataset (AMP2026), a multi-platform marine robotics dataset collected across multiple field deployments designed to support research in two primary areas: multi-view tracking and marine environment mapping. The dataset includes synchronized data from aerial drones, boat-mounted cameras, and submerged robotic platforms, along with associated localization and telemetry information. The goal of this work is to provide a publicly available dataset enabling research in marine perception and multi-robot observation scenarios. This paper describes the data collection methodology, sensor configurations, dataset organization, and intended research tasks supported by the dataset.
2026-05-13
Conference on Robots and Vision (publié)
doi.org
arxiv.org
On the Coverage of Planar Worlds with Simulated Mobile Ad Hoc Networks
Edwin Meriaux
Shuo Wen
Louis-Roy Langevin
Antonio Lorı́a
Gregory Dudek
In this paper, we study the online deployment of mobile ad hoc networks (MANETs) to achieve complete sensing coverage in initially unknown p… (voir plus)lanar worlds while maintaining connectivity, as formalized by the Partially Observable Cooperative Guard Art Gallery Problem (POCGAGP). While prior work provided strong guarantees in orthogonal worlds, many realistic worlds exhibit arbitrary polygonal or curvilinear boundaries that violate these assumptions. We extend the POCGAGP framework and evaluation to such settings and show that the target-selection step of the DADENCE algorithm can be implemented as a neighbor-only average-consensus process. Through evaluation on over 1,500 test cases spanning a wide range of geometric complexities, we demonstrate that DADENCE achieves superior robustness and agent efficiency compared to five benchmark algorithms across both polygonal and curvilinear worlds.
2025-12-31
2026 (prépublication)
openalex.org
The Prestige: Benchmarking Cognitive Visual Reasoning using Magic Tricks
Shuo Wen
Beixi Du
Edwin Meriaux
Junming Shi
Chloe Si
David Meger
Doina Precup
Gregory Dudek
2025-12-31
Neural Information Processing Systems (Accept (poster))
openreview.net
openreview.net
On Mobile Ad Hoc Networks for Coverage of Partially Observable Worlds
Edwin Meriaux
Shuo Wen
Louis-Roy Langevin
Doina Precup
Antonio Lor'ia
Gregory Dudek
2025-12-09
ArXiv (prépublication)
doi.org
arxiv.org