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Andreagiovanni Reina

9 accepted papers

2026

AutoPercep: A Pipeline for Onboard Neighbor Position Estimation Toward Large-Scale Swarm Robotics

Ruiheng Wu, Simay Atasoy Bingöl, Oliver Deussen, Heiko Hamann, Iain D. Couzin, Andreagiovanni Reina +1
ICRA 2026poster

Autonomous mobile robots must know each other's positions to coordinate their actions and motion. Beyond collision avoidance, relative position estimation is essential for spatial coordination tasks such as collective motion, leader–follower dynamics, or formation control.To overcome the scalability…

Cited by 0code ↗Scholar ↗
2026

Multi-Robot Obstacle-Aware Shepherding of Non-Cohesive Target Agents

Cinzia Tomaselli, Stefano Covone, Andreagiovanni Reina, Mario Di Bernardo
ICRA 2026poster

This paper presents a novel control strategy for multi-agent shepherding of non-cohesive targets in obstacle-rich environments. Unlike previous approaches that assume cohesive flocking behavior, our method handles targets that interact only with nearby herders through repulsive forces and exhibit no…

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2024

Do We Run Large-scale Multi-Robot Systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling

Jonas Kuckling, Robin Luckey, Viktor Avrutin, Andrew Vardy, Andreagiovanni Reina, Heiko Hamann
ICRA 2024poster

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing be…

Cited by 5Source ↗Scholar ↗
2024

Miscommunication between robots can improve group accuracy in best-of-n decision-making

Raina Zakir, Marco Dorigo, Andreagiovanni Reina
IROS 2024poster

Making fast and accurate consensus decisions through local communication and decentralised control in a swarm of simple robots can be a very challenging endeavour. In swarms of robots with limited capabilities, consensus decisions can be made using simple voting rules. In our study, the robots use r…

Cited by 1Source ↗Scholar ↗
2023

A Generic Framework for Byzantine-Tolerant Consensus Achievement in Robot Swarms

Hanqing Zhao, Alexandre Pacheco, Volker Strobel, Andreagiovanni Reina, Xue Liu, Gregory Dudek +1
IROS 2023poster

Recent studies show that some security features that blockchains grant to decentralized networks on the internet can be ported to swarm robotics. Although the integration of blockchain technology and swarm robotics shows great promise, thus far, research has been limited to proof-of-concept scenario…

Cited by 15Source ↗Scholar ↗
2023

Multi-Swarm Interaction Through Augmented Reality for Kilobots

Luigi Feola, Andreagiovanni Reina, Mohamed S. Talamali, Vito Trianni
RA-L 2023

Research with swarm robotics systems can be complicated, time-consuming, and often expensive in terms of space and resources. The situation is even worse for studies involving multiple, possibly heterogeneous robot swarms. Augmented reality can provide an interesting solution to these problems, as d

Cited by 5Source ↗Scholar ↗
2019

Improving collective decision accuracy via time-varying cross-inhibition

Mohamed S. Talamali, James A. R. Marshall, Thomas Bose, Andreagiovanni Reina
ICRA 2019poster

We investigate decentralised decision-making, in which a robot swarm is tasked with selecting the best-quality option among a set of alternatives. Individual robots are simplistic as they only perform diffusive search, make local noisy estimates of the options' quality, and exchange information with…

Cited by 35Source ↗Scholar ↗
2017

ARK: Augmented Reality for Kilobots

Andreagiovanni Reina, Alex J. Cope, Eleftherios Nikolaidis, James A. R. Marshall, Chelsea Sabo
RA-L 2017

Working with large swarms of robots has challenges in calibration, sensing, tracking, and control due to the associated scalability and time requirements. Kilobots solve this through their ease of maintenance and programming, and are widely used in several research laboratories worldwide where their

Cited by 62Source ↗Scholar ↗
2016

Emergence of Consensus in a Multi-Robot Network: From Abstract Models to Empirical Validation

Vito Trianni, Daniele De Simone, Andreagiovanni Reina, Andrea Baronchelli
RA-L 2016

Consensus dynamics in decentralised multiagent systems are subject to intense studies, and several different models have been proposed and analyzed. Among these, the naming game stands out for its simplicity and applicability to a wide range of phenomena and applications, from semiotics to engineeri

Cited by 47Source ↗Scholar ↗