Multi-objective Grasshopper Optimization Algorithm for Robot Path Planning in Static Environments
Yazarlar (2)
Dr. Öğr. Üyesi Zehra ELMI İSti̇Nye Üni̇Versi̇Tesi̇, Türkiye
Prof. Dr. Mehmet Önder Efe Hacettepe Üni̇Versi̇Tesi̇, Türkiye
| Bildiri Türü |
Tebliğ/Bildiri
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Bildiri Dili | İNgilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Web of Science Kapsamındaki Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/ICIT.2018.8352184 | ||
| Kongre Adı | the 19th IEEE International Conference on Industrial Technology(ICIT 2018) | ||
| Kongre Tarihi | 20-02-2018 / 22-02-2018 | ||
| Basıldığı Ülke | Fransa | Basıldığı Şehir | Lyon |
| Bildiri Linki | https://ieeexplore.ieee.org/abstract/document/8352184 | ||
| UAK Araştırma Alanları |
Yapay Zeka
Robotik
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| Özet |
| Finding the most appropriate path in robot navigation has been an interesting challenge in recent years. A number of different techniques have been proposed to address this problem. Heuristic methods are one of them that have been efficiently used in many complex and multi-dimensional optimization problems. In this paper, we present a new algorithm for robot path planning in a static environment. The main aim is to use a multi objective method to minimize several metrics such as cost, distance, energy or time. Distance, path smoothness and robot path planning time is optimized in the current work. The contribution of this work is to calculate an appropriate fitness function at each iteration to achieve the best solution. The obtained result is compared with the Particle Swarm Optimization (PSO) algorithm. The proposed algorithm displays better performance characteristics in terms of time and path smoothness … |
| Anahtar Kelimeler |
| Grasshopper Optimization Algorithm | Mobile Multi-Robot | Obstacle Avoidance | Path Planning | Static Environment |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 33 |
| Google Scholar | 43 |