Electronics Optics & Control, Volume. 31, Issue 9, 6(2024)

An Improved Particle Swarm Hybrid Path Planning Algorithm with Hill Climbing Strategy

KONG Pengfei
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    References(17)

    [2] [2] ZHANG H YLIN M WCHEN A X.Path planning for the mobile robot:a review [J].Symmetry201810(10):450.

    [3] [3] CHENG C XSHA Q XHE Bet al.Path planning and obstacle avoidance for AUV:a review[J].Ocean Engineering2021235(7):109355.

    [5] [5] HICHRI BGALLALA AGIOVANNINI Fet al.Mobile robots path planning and mobile multirobots control:a review [J].Robotica202240(12):42574270.

    [6] [6] PATLE B KGANESH B LANISH Pet al.A review:on path planning strategies for navigation of mobile robot [J].Defence Technology201915(4):582606.

    [7] [7] TUAN DGEORGIA CJAN Pet al.MonteCarlo robot path planning [J].IEEE Robotics and Automation Letters20227(4):1121311220.

    [8] [8] HAN J.An efficient approach to 3D path planning[J].Information Sciences2019478.doi:10.1016/j.ins.2018.11.045.

    [9] [9] SHAO J HFAN Z HHUANG Y Yet al.Multiobjective optimization of doublewalled steel cofferdams based on response surface methodology and particle swarm optimization algorithm[J].Structures202349(1):256266.

    [10] [10] LIU X HZHANG D GZHANG Tet al.A new path plan method based on hybrid algorithm of reinforcement learning and particle swarm optimization [J].Engineering Computations202139(3):9931091.

    [11] [11] SONG B YWANG Z DZOU L.An improved PSO algorithm for smooth path planning of mobile robots using continuous highdegree Bezier curve [J].Applied Soft Computing2021100.doi:10.1016/j.asoc.2021.106960.

    [12] [12] TIAN S SLI Y XKANG Y Let al.Multirobot path planning in wireless sensor networks based on jump mechanism PSO and safety gap obstacle avoidance [J].Future Generation Computer Systems2020118(6):3747.

    [13] [13] MIAO KMAO X LLI C.Individualism of particles in particle swarm optimization[J].Applied Soft Computing Journal201983.doi:10.1016/j.asoc.2019.105619.

    [15] [15] GAO YLIU JHU M Qet al.A new path evaluation method for path planning with localizability [J].IEEE Access 20197:162583162597.

    [16] [16] KUZNETSOV AFRONTONI EROMEO Let al.Optimizing hill climbing algorithm for Sboxes generation[J].Electronics202312(10):2338.

    [20] [20] WANG Y BBAI PLIANG X Let al.Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms[J].IEEE Access2019 7:105086105099.

    [22] [22] XU LCAO M YSONG B Y.A new approach to smooth path planning of mobile robot based on quartic bezier transition curve and improved PSO algorithm [J].Neurocomputing2022473(C):98106.

    [25] [25] CHEN C FZAIN A MMO L Pet al.A new hybrid algorithm based on ABC and PSO for function optimization[J].IOP Conference Series:Materials Science and Engineering2020864.doi:10.1088/1757899X/864/1/012065.

    [26] [26] BEED RROY ASARKAR Set al.A hybrid multiobjective tour route optimization algorithm based on particle swarm optimization and artificial bee colony optimization[J].Computational Intelligence202036(3):884909.

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    KONG Pengfei. An Improved Particle Swarm Hybrid Path Planning Algorithm with Hill Climbing Strategy[J]. Electronics Optics & Control, 2024, 31(9): 6

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    Paper Information

    Received: Oct. 8, 2023

    Accepted: --

    Published Online: Oct. 22, 2024

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2024.09.002

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