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      Closed-Loop Motion Control of Robotic Swarms – A Tether-Based Strategy

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          A review on genetic algorithm: past, present, and future

          In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.
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            Sampling-based algorithms for optimal motion planning

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              Swarm robotics: a review from the swarm engineering perspective

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                Author and article information

                Contributors
                Journal
                IEEE Transactions on Robotics
                IEEE Trans. Robot.
                Institute of Electrical and Electronics Engineers (IEEE)
                1552-3098
                1941-0468
                December 2022
                December 2022
                : 38
                : 6
                : 3564-3581
                Affiliations
                [1 ]Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
                Article
                10.1109/TRO.2022.3181055
                75bbd9ff-1057-4a25-b316-f6251d0da1e0
                © 2022

                https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

                History

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