Efficiency Boost: Service Robot Path Planning with Grey Wolf Optimization

被引：1

作者：

Husakovic, Anel ^{[1
]}

Banjanovic-Mehmedovic, Lejla ^{[2
]}

Konjic, Tatjana ^{[2
]}

机构：

[1] Eacon Doo, Zenica, Bosnia & Herceg

[2] Univ Tuzla, Fac Elect Engn, Tuzla, Bosnia & Herceg

来源：

2024 23RD INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA, INFOTEH | 2024年

关键词：

path planning; optimization; service robot; great wolf optimizer; Industry; 4.0; MOBILE ROBOT;

D O I：

10.1109/INFOTEH60418.2024.10495949

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the era of Industry 4.0, service robot path planning has emerged as a pivotal element in the optimization of logistic tasks within manufacturing, warehousing and service applications. In this context, the adoption of advanced path planning algorithms, such as the Grey Wolf Optimizer (GWO) swarm algorithm, play a key role in enabling these robots to navigate through complex environments with precision and agility. Harnessing the power of bio-inspired algorithms, our framework establishes a methodical and effective approach to the intricate task of service robot path planning.

引用

页数：6

共 17 条

[1] Classical and Heuristic Approaches for Mobile Robot Path Planning: A Survey [J].