An Improved Robot Path Planning Algorithm

Xuesong Yan
<span title="2012-12-01">2012</span> <i title="Universitas Ahmad Dahlan"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/avuzjspx3nh5lboz3nsmpd3ba4" style="color: black;">TELKOMNIKA (Telecommunication Computing Electronics and Control)</a> </i> &nbsp;
Abstrak Robot path planning adalah masalah NP.Metode optimasi tradisional tidak efektif untuk mengatasinya. Algoritma genetika tradisional terjebak ke dalam minimum lokal dengan mudah. Oleh karena itu, didasarkan pada algoritma genetika yang sederhana dan menggabungkan ideologi dasar metode desain orthogonal kemudian diterapkan ke inisialisasi populasi, menggunakan mekanisme elit antargenerasi, serta pengenalan operator pencarian adaptif lokal untuk mencegah terjebak ke dalam minimum lokal dan
more &raquo; ... eningkatkan kecepatan konvergensi untuk membentuk algoritma genetik baru. Melalui serangkaian percobaan numerik, algoritma baru telah terbukti efisien. Kami juga menggunakan algoritma yang diusulkan untuk memecahkan masalah robot path planning dan hasil penelitian menunjukkan bahwa algoritma baru terbuktiefisien untuk memecahkan masalah robot path planning dan jalan terbaik biasanya dapat ditemukan. Kata kunci: optimalisasi fungsi, algoritma genetika, inisialisasi ortogonal, perencanaan robot jalan Abstract Robot path planning is a NP problem. Traditionaloptimization methods are not very effective to solve it. Traditional genetic algorithm trapped into the local minimum easily. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal design method then applied it to the population initialization, using the intergenerational elite mechanism, as well as the introduction of adaptive local search operator to prevent trapped into the local minimum and improvethe convergence speed to form a new genetic algorithm. Through the series of numerical experiments, the new algorithm has been proved to be efficiency.We also use the proposed algorithm to solve the robot path planning problem and the experiment results indicated that the new algorithm is efficiency for solving the robot path planning problems and the best path usually can be found.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.12928/telkomnika.v10i4.412">doi:10.12928/telkomnika.v10i4.412</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kbum6hbsyrcsncc6lujstjgaqi">fatcat:kbum6hbsyrcsncc6lujstjgaqi</a> </span>
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