scholarly journals Towards a formal analysis of the multi-robot task allocation problem using set theory

2021 ◽  
Vol 10 (2) ◽  
pp. 1092-1104
Author(s):  
Farouq Zitouni ◽  
Ramdane Maamri ◽  
Saad Harous
Keyword(s):  
Set Theory ◽  
Task Allocation ◽  
Formal Analysis ◽  
Efficient Solutions ◽  
Allocation Problem ◽  
Allocation Problems ◽  
Robot Systems ◽  
Robot Task ◽  
Large Groups ◽  
Multi Robot

Nowadays, the multi-robot task allocation problem is one of the most challenging problems in multi-robot systems. It concerns the optimal assignment of a set of tasks to several robots while optimizing a given criterion subject to some constraints. This problem is very complex, particularly when handling large groups of robots and tasks. We propose a formal analysis of the task allocation problem in a multi-robot system, based on set theory concepts. We believe that this analysis will help researchers understand the nature of the problem, its time complexity, and consequently develop efficient solutions. Also, we used that formal analysis to formulate two well-known taxonomies of multi-robot task allocation problems. Finally, a generic solving scheme of multi-robot task allocation problems is proposed and illustrated on assigning papers to reviewers within a journal.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

scholarly journals A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems

2004 ◽  
Vol 23 (9) ◽  
pp. 939-954 ◽  
Author(s):  
Brian P. Gerkey ◽  
Maja J. Matarić
Keyword(s):  
Task Allocation ◽  
Formal Analysis ◽  
Robot Systems ◽  
Multi Robot

FA–QABC–MRTA: a solution for solving the multi-robot task allocation problem

2019 ◽  
Vol 12 (4) ◽  
pp. 407-418 ◽  
Author(s):  
Farouq Zitouni ◽  
Ramdane Maamri ◽  
Saad Harous
Keyword(s):  
Task Allocation ◽  
Allocation Problem ◽  
Robot Task ◽  
Multi Robot
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