Cost Functions of Crabs: Applications of Hermit Crab Shell Exchange Behavior to Vacancy Chain Modelling

Vacancy chain systems function as a method of resource distribution in domains such as housing and labor markets. Hermit crabs also employ vacancy chains as a method of shell exchange. Application of vacancy chain modelling in engineering has been attempted, but numerous flaws exist in the developed vacancy chain scheduling algorithm. This work addresses the lack of an appropriate vacancy chain cost function by developing a generalizable cost function based on hermit crab shell exchange behavior. The cost function’s purpose is enabling development of realistic engineering experiments and models based on real-world vacancy chain systems

On the problem of task planning in Multi-Robot Systems

International audienceMulti-robot task planning (MRTP) is one of the fundamental problems for multi-robot systems. An important question facing this research topic is, which robot should execute which task so as the expected overall system performance can be maximized? Many approaches have been proposed for such a purpose. This paper investigates the existing works in the field. The approaches have been surveyed and some representatives are compared with detailed results. A brief discussion and further research perspectives are also given at the end of the paper

Statikus bluetooth kommunikációs láncon alapuló, multi-robot területfelfedező algoritmus

A cikkben bemutatunk egy általunk kifejlesztett területfelderítő algoritmust, mely robosztus, sok robotból álló rendszerek esetén is működik. A robotok bluetoothon keresztül kommunikálnak, kommunikáció szempontjából lánccá szerveződnek, a lánc egyik vége rögzített és a felderítés alatt kényszer feltétel az, hogy a szomszédos robotok semmiképp sem távolodhatnak egymás kommunikációs hatósugarából. Az írásban egyszerűen bizonyítjuk, hogy az általunk készített algoritmus optimális akadálymentes területeken, azaz a lehető legnagyobb területet fedezi fel a lehetséges legkisebb időráfordítással. Bemutatunk egy tesztet, melyben összehasonlítjuk az általunk ajánlott eljárást két referencia eljárással, falszerű akadályokkal ellátott területeken is. A cikkben az általunk készített algoritmust nem csak képernyő szimulátorral teszteltük, hanem implementáltuk valós Dual NXT robotokból álló robotcsoportra is

Multi-Agent Task Allocation in Complementary Teams: A Hunter and Gatherer Approach

Consider a dynamic task allocation problem, where tasks are unknowingly distributed over an environment. This paper considers each task comprised of two sequential subtasks: detection and completion, where each subtask can only be carried out by a certain type of agent. We address this problem using a novel nature-inspired approach called "hunter and gatherer". The proposed method employs two complementary teams of agents: one agile in detecting (hunters) and another skillful in completing (gatherers) the tasks. To minimize the collective cost of task accomplishments in a distributed manner, a game-theoretic solution is introduced to couple agents from complementary teams. We utilize market-based negotiation models to develop incentive-based decision-making algorithms relying on innovative notions of "certainty and uncertainty profit margins". The simulation results demonstrate that employing two complementary teams of hunters and gatherers can effectually improve the number of tasks completed by agents compared to conventional methods, while the collective cost of accomplishments is minimized. In addition, the stability and efficacy of the proposed solutions are studied using Nash equilibrium analysis and statistical analysis respectively. It is also numerically shown that the proposed solutions function fairly, i.e. for each type of agent, the overall workload is distributed equally.Comment: 15 pages, 12 figure

Multi-robot preemptive task scheduling with fault recovery: a novel approach to automatic logistics of smart factories

This paper presents a novel approach for Multi-Robot Task Allocation (MRTA) that introduces priority policies on preemptive task scheduling and considers dependencies between tasks, and tolerates faults. The approach is referred to as Multi-Robot Preemptive Task Scheduling with Fault Recovery (MRPF). It considers the interaction between running processes and their tasks for management at each new event, prioritizing the more relevant tasks without idleness and latency. The benefit of this approach is the optimization of production in smart factories, where autonomous robots are being employed to improve efficiency and increase flexibility. The evaluation of MRPF is performed through experimentation in small-scale warehouse logistics, referred to as Augmented Reality to Enhanced Experimentation in Smart Warehouses (ARENA). An analysis of priority scheduling, task preemption, and fault recovery is presented to show the benefits of the proposed approach.This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001 and in part by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).info:eu-repo/semantics/publishedVersio

A Survey and Analysis of Multi-Robot Coordination

International audienceIn the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper

Nuevas metodologías para la asignación de tareas y formación de coaliciones en sistemas multi-robot

Este trabajo analiza la idoneidad de dos de los principales métodos de asignación de tareas en entornos con restricciones temporales. Se pondrá de manifiesto que ambos tipos de mecanismos presentan carencias para tratar tareas con deadlines, especialmente cuando los robots han de formar coaliciones. Uno de los aspectos a los que esta tesis dedica mayor atención es la predicción del tiempo de ejecución, que depende, entre otros factores, de la interferencia física entre robots. Este fenómeno no se ha tenido en cuenta en los mecanismos actuales de asignación basados en subastas. Así, esta tesis presenta el primer mecanismo de subastas para la creación de coaliciones que tiene en cuenta la interferencia entre robots. Para ello, se ha desarrollado un modelo de predicción del tiempo de ejecución y un nuevo paradigma llamado subasta doble. Además, se han propuesto nuevos mecanismos basados en swar