A unified Lloyd-based framework for multi-agent collective behaviours

Boldrer, Manuel; Palopoli, Luigi; Fontanelli, Daniele

doi:10.1016/j.robot.2022.104207

Cited by 7 publications

(10 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As described in Proposition 2 in Appendix A-B, the convergence of the proposed algorithm is achieved under specific conditions. We also compared the performance of αCVT with other recent coverage control methods presented in [25], [26] and [31]. The algorithm in [25] and [31] only concerned nonconvex environments with obstacles.…”

Section: ) Simulation Resultsmentioning

confidence: 99%

“…It is compared with iCVT combined with projection (referred to as 'iCVT+Projection') [11] -an iterative scheme that performs CVT and projection algorithm at every iteration. Section III-B also includes additional compar- isons with two other recent works [25], [26]. The size of the 2D domains was 200 × 200 pixels.…”

Section: Algorithm Applications and Evaluationsmentioning

confidence: 99%

“…In [25], the agents' position changed the density function of the environment locally. Similarly, a time-varying density function in [26] enabled the agents to visit the invisible regions behind obstacles. It adopted an adaptive static coverage scheme similar to the convex weighted Voronoi diagram introduced in [27].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Centroidal Voronoi Tessellation With Agent Dropout and Reinsertion for Multi-Agent Non-Convex Area Coverage

Lee,

Lee

2024

IEEE Access

View full text Add to dashboard Cite

Voronoi diagrams are widely used for area partitioning and coverage control. However, their application in non-convex domains typically requires additional computational procedures, such as the application of diffeomorphism, geodesic distance calculations, or incorporation of local markers. These techniques tend to be challenging to extend across diverse non-convex domains. This paper introduces the adaptive centroidal Voronoi tessellation (αCVT) algorithm, integrating iterative centroidal Voronoi tessellation (iCVT) with a novel agent dropout and reinsertion strategy to enhance area coverage control in non-convex domains. This approach demonstrates versatility across varied environments without requiring complex computational processes. The algorithm's efficacy is validated through a series of simulations encompassing non-convex domains with disjoint target areas, obstacles, and shape constraints for both homogeneous and heterogeneous agents. Additionally, the αCVT algorithm is extended for real-time coverage control scenarios. Performance metrics are employed to gauge the distribution of partitioned Voronoi regions and the overall coverage of the target areas, and the results show improved performance compared to the method without adopting the agent dropout and reinsertion strategy.INDEX TERMS Area partitioning, non-convex area coverage control, multi-agent system, Voronoi tessellation.

show abstract

Section: ) Simulation Resultsmentioning

confidence: 99%

Section: Algorithm Applications and Evaluationsmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Centroidal Voronoi Tessellation With Agent Dropout and Reinsertion for Multi-Agent Non-Convex Area Coverage

Lee,

Lee

2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Our claim is that, by modifying the geometry of the cell V i and by properly designing a weighting function φ i (q), we can obtain an efficient and effective algorithm for multirobot motion planning and control. Notice that, while the cell geometry to provide safety was introduced by the basic LB algorithm [53], [57]- [60], one of the novelty introduced in this work, besides the use of the algorithm as a safety layer for learning-based algorithm and the introduction of an MPC formulation to deal with dynamical constraint, is the addition of rules in the shaping of the weighting function φ i (q), which are crucial in order to increase the performance and provide convergence guarantees to the goal positions.…”

Section: Approachmentioning

confidence: 99%

Time-Inverted Kuramoto Model Meets Lissajous Curves: Multi-Robot Persistent Monitoring and Target Detection

Boldrer

Lyons

Palopoli

et al. 2023

IEEE Robot. Autom. Lett.

Self Cite

View full text Add to dashboard Cite

This paper presents a distributed rule-based Lloyd algorithm (RBL) for multi-robot motion planning and control. The main limitations of the basic Loyd-based algorithm (LB) concern deadlock issues and the failure to address dynamic constraints effectively. Our contribution is twofold. First, we show how RBL is able to provide safety and convergence to the goal region without relying on communication between robots, nor neighbors control inputs, nor synchronization between the robots. We considered both case of holonomic and non-holonomic robots with control inputs saturation. Second, we show that the Lloyd-based algorithm (without rules) can be successfully used as a safety layer for learning-based approaches, leading to nonnegligible benefits. We further prove the soundness, reliability, and scalability of RBL through extensive simulations, an updated comparison with the state of the art, and experimental validations on small-scale car-like robots.

show abstract

“…Distributed control of multi-agent systems is a very active research area, both in the control and in the robotics communities. In these fields, one of the topics that received the most attention is the emergence of collective behaviours from the combination of local interaction rules [1], [2]. The Kuramoto Model [3] falls in this class of models.…”

Section: Introductionmentioning

confidence: 99%

Time-Inverted Kuramoto Dynamics for κ-Clustered Circle Coverage

Boldrer

Riz

Pasqualetti

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

In this paper we analyse the equilibrium configurations for the time-inverted Kuramoto Model with homogeneous agents and a fixed ring topology, where time-inverted means that the coupling between the different states is via a negative factor. This model exhibits a dual behaviour with respect to the classic Kuramoto Model with a positive copuling. In the paper, we show the existence of two possibile stable equilibrium configurations: the splay state formation (1-clustered coverage) and the deployment in clusters (κ-clustered coverage). We provide sufficient conditions for the splay state formation and a stability analysis for the networked system. Moreover, we provide some initial results towards the controllability of the final equilibrium configurations. In particular, we lay the foundations to understand the conditions to switch between stable equilibria.

show abstract

A unified Lloyd-based framework for multi-agent collective behaviours

Cited by 7 publications

References 56 publications

Adaptive Centroidal Voronoi Tessellation With Agent Dropout and Reinsertion for Multi-Agent Non-Convex Area Coverage

Adaptive Centroidal Voronoi Tessellation With Agent Dropout and Reinsertion for Multi-Agent Non-Convex Area Coverage

Time-Inverted Kuramoto Model Meets Lissajous Curves: Multi-Robot Persistent Monitoring and Target Detection

Time-Inverted Kuramoto Dynamics for κ-Clustered Circle Coverage

Contact Info

Product

Resources

About