Review of methodologies and tasks in swarm robotics towards standardization

Nedjah, Nadia; Silva, Luneque

doi:10.1016/j.swevo.2019.100565

Cited by 95 publications

(72 citation statements)

References 95 publications

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“…e algorithm [19,20] can be applied for a clear graph based on a complete enumeration of all vertices and edges of the graph and extend its application to a fuzzy graph with the selection of the maximum bipartite parts of the graph.…”

Section: Target Assignment Model Graph Theory Uses Methodsmentioning

confidence: 99%

Methods Research and Software Development for Parameters Formalization of the Assignment Task Applicable to the Target Distribution

Beloglazov

Finaev

Soloviev

et al. 2020

Journal of Robotics

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The paper discusses the solution of the assignment task between two groups of mobile (MR) objects. The assignment task is to determine the purpose of MR to each other when playing football. This article analyzes well-known works devoted to the tasks of assignments, and the relevance of research in this area is noted. The task of target distribution is successfully solved with a small degree of uncertainty. The urgency of further research to solve the problem of target distribution in conditions of uncertainty is substantiated. The model of target assignment is considered. The basis of the model is a bipartite graph. The vertices of a bipartite graph are defined by the properties of MR. One group of MR is assigned red color and the other one group is blue. The properties of the mobile objects are formally determined by the membership grades given by the experts. Identification of a bipartite graph is a solution to the assignment problem. When the problem of target distribution on a bipartite graph is solved, the criterion of the maximum degree of bipartite is applied. Formulas are given to determine the degree of bipartite, taking into account the number of vertices in the graph and the weight of each edge in two fractions of the graph. The study of the target distribution model was carried out by the simulation method. A program is developed to solve the problem of assignments. Properties and degrees of belonging of properties of red and blue MR are set for carrying out researches. The program allows you to produce research and under equality of red and blue MR, and under their inequality. The analysis of modeling results is carried out.

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Section: Target Assignment Model Graph Theory Uses Methodsmentioning

confidence: 99%

Methods Research and Software Development for Parameters Formalization of the Assignment Task Applicable to the Target Distribution

Beloglazov

Finaev

Soloviev

et al. 2020

Journal of Robotics

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“…To mathematically formulate the above logic, a confidence function (C n T ( r, t)) is defined in (4). Specifically, the function C n T is a value that indicates how good is position r for a node n targeted to task T to stay in.…”

Section: Nodementioning

confidence: 99%

“…Robotic Swarms can be categorized to homogeneous and heterogeneous based on the differences between the type of task that the individual nodes are able to perform [4]. Specifically, swarms where robots of different design or functionality coexist are coined as heterogeneous [5].…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Bioinspired Non-Discrete Model for Autonomous Swarm Aggregation Dynamics

Oikonomou

Pappas

2020

Applied Sciences

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In this paper a microscopic, non-discrete, mathematical model based on stigmergy for predicting the nodal aggregation dynamics of decentralized, autonomous robotic swarms is proposed. The model departs from conventional applications of stigmergy in bioinspired path-finding optimization, serving as a dynamic aggregation algorithm for nodes with limited or no ability to perform discrete logical operations, aiding in agent miniaturization. Time-continuous simulations were developed and carried out where nodal aggregation efficiency was evaluated using the following metrics: time to aggregation equilibrium, agent spatial distribution within aggregate (including average inter-nodal distance, center of mass of aggregate deviation from target), and deviation from target agent number. The system was optimized using cost minimization of the above factors through generating a random set of cost datapoints with varying initial conditions (number of aggregates, agents, field dimensions, and other specific agent parameters) where the best-fit scalar field was obtained using a random forest ensemble learning strategy and polynomial regression. The scalar cost field global minimum was obtained through basin-hopping with L-BFGS-B local minimization on the scalar fields obtained through both methods. The proposed optimized model describes the physical properties that non-digital agents must possess so that the proposed aggregation behavior emerges, in order to avoid discrete state algorithms aiming towards developing agents independent of digital components aiding to their miniaturization.

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“…Extensive research has been carried out to determine, in all three sub-models, the computational boundaries as well as the impact that factors such as presence/absence of common coordinate system, movement rigidity (i.e., being able to always reach the destination), etc., have on computability and complexity (e.g., see [3], [6], [14]- [16], [18], [28], [29], [31], and the recent books and chapters therein [12], [13]). Although this research is highly theoretical, its influence is sometimes felt in more practical settings (e.g., see [5], [19], [20], [22], [27] in the recent literature).…”

Section: A Frameworkmentioning

confidence: 99%

Forming Sequences of Patterns With Luminous Robots

et al. 2020

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The extensive studies on computing by a team of identical mobile robots operating in the plane in Look-Compute-Move cycles have been carried out mainly in the traditional OBLOT model, where the robots are silent (have no communication capabilities) and oblivious (in a cycle, they have no memory previous cycles). To partially overcome the limits of obliviousness and silence while maintaining some of their advantages, the stronger model of luminous robots, LUMI, has been introduced where the robots, otherwise oblivious and silent, carry a visible light that can take a number of different colors; a color can be seen by observing robots, and persists from a cycle to the next. In the study of the computational impact of lights, an immediate concern has been to understand and determine the additional computational strength of LUMI over OBLOT. Within this line of investigation, we examine the problem of forming a sequence of geometric patterns, PATTERNSEQUENCEFORMATION. A complete characterization of the sequences of patterns formable from a given starting configuration has been determined in the OBLOT model. In this paper, we study the formation of sequences of patterns in the LUMI model and provide a complete characterization. The characterization is constructive: our universal protocol forms all formable sequences, and it does so asynchronously and without rigidity. This characterization explicitly and clearly identifies the computational strength of LUMI over OBLOT with respect to the PATTERNSEQUENCEFORMATION problem. INDEX TERMS Autonomous mobile robots, distributed computing, oblivious, pattern formation, sequence of patterns, visible lights.

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Review of methodologies and tasks in swarm robotics towards standardization

Cited by 95 publications

References 95 publications

Methods Research and Software Development for Parameters Formalization of the Assignment Task Applicable to the Target Distribution

Methods Research and Software Development for Parameters Formalization of the Assignment Task Applicable to the Target Distribution

Decentralized Bioinspired Non-Discrete Model for Autonomous Swarm Aggregation Dynamics

Forming Sequences of Patterns With Luminous Robots

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