Literature DB >> 33879973

Multi-Robot Coordination Analysis, Taxonomy, Challenges and Future Scope.

Janardan Kumar Verma1, Virender Ranga1.   

Abstract

Recently, Multi-Robot Systems (MRS) have attained considerable recognition because of their efficiency and applicability in different types of real-life applications. This paper provides a comprehensive research study on MRS coordination, starting with the basic terminology, categorization, application domains, and finally, give a summary and insights on the proposed coordination approaches for each application domain. We have done an extensive study on recent contributions in this research area in order to identify the strengths, limitations, and open research issues, and also highlighted the scope for future research. Further, we have examined a series of MRS state-of-the-art parameters that affect MRS coordination and, thus, the efficiency of MRS, like communication mechanism, planning strategy, control architecture, scalability, and decision-making. We have proposed a new taxonomy to classify various coordination approaches of MRS based on the six broad dimensions. We have also analyzed that how coordination can be achieved and improved in two fundamental problems, i.e., multi-robot motion planning, and task planning, and in various application domains of MRS such as exploration, object transport, target tracking, etc.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

Entities:  

Keywords:  Cooperation; Coordination; Exploration and mapping; Multi-robot motion planning; Multi-robot system; Multi-robot task planning; Object transport and manipulation; Target observation

Year:  2021        PMID: 33879973      PMCID: PMC8051283          DOI: 10.1007/s10846-021-01378-2

Source DB:  PubMed          Journal:  J Intell Robot Syst        ISSN: 0921-0296            Impact factor:   2.646


  10 in total

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Journal:  Artif Life       Date:  2008       Impact factor: 0.667

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Journal:  IEEE Trans Neural Netw       Date:  2008-12

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Authors:  Jennifer L Scheid; Katelyn A Carr; Henry Lin; Kelly D Fletcher; Lara Sucheston; Prashant K Singh; Robbert Salis; Richard W Erbe; Myles S Faith; David B Allison; Leonard H Epstein
Journal:  Physiol Behav       Date:  2014-04-24

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Authors:  Asif Khan; Bernhard Rinner; Andrea Cavallaro
Journal:  IEEE Trans Cybern       Date:  2016-12-01       Impact factor: 11.448

9.  Prescribed Performance Adaptive Fuzzy Containment Control for Nonlinear Multiagent Systems Using Disturbance Observer.

Authors:  Wei Wang; Hongjing Liang; Yingnan Pan; Tieshan Li
Journal:  IEEE Trans Cybern       Date:  2020-02-25       Impact factor: 11.448

10.  Mobile robots exploration through cnn-based reinforcement learning.

Authors:  Lei Tai; Ming Liu
Journal:  Robotics Biomim       Date:  2016-12-21
  10 in total
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Journal:  PLoS One       Date:  2022-09-15       Impact factor: 3.752

  1 in total

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