4 papers
Swarming Without an Anchor (SWA): Robot Swarms Adapt Better to Localization Dropouts Then a Single Robot
Jiri Horyna, Roland Jung, Stephan Weiss +2
In this paper, we present the Swarming Without an Anchor (SWA) approach to state estimation in swarms of Unmanned Aerial Vehicles (UAVs) experiencing ego-localization dropout, wher…
MinionsLLM: a Task-adaptive Framework For The Training and Control of Multi-Agent Systems Through Natural Language
Andres Garcia Rincon, Eliseo Ferrante
This paper presents MinionsLLM, a novel framework that integrates Large Language Models (LLMs) with Behavior Trees (BTs) and Formal Grammars to enable natural language control of m…
Emergent Heterogeneous Swarm Control Through Hebbian Learning
Fuda van Diggelen, Tugay Alperen Karagüzel, Andres Garcia Rincon +3
In this paper, we introduce Hebbian learning as a novel method for swarm robotics, enabling the automatic emergence of heterogeneity. Hebbian learning presents a biologically inspi…
A Minimalistic 3D Self-Organized UAV Flocking Approach for Desert Exploration
Thulio Amorim, Tiago Nascimento, Akash Chaudhary +2
In this work, we propose a minimalistic swarm flocking approach for multirotor unmanned aerial vehicles (UAVs). Our approach allows the swarm to achieve cohesively and aligned floc…