Author
Mohammadzadeh, A., Firouzi, Behnam
Publication Date
2023-04
Publication Place
-
Springer
Subject
Biogeographical algorithm, Genetic algorithm, Particle swarm optimization, Path following, Robot
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
1868-5137
Record ID
eea25324-28a6-4b11-b7db-5bcf77238e29
Date
2023-04
Sample Text
Robot routing is one of the most important topics in mobile robotics. The goal is to find a continuous path from an initial position to an end destination that is collision-free and optimal or near-optimal. Due to the growing trend of using automatic moving tools in industrial automation, and their application for various purposes such as transportation of goods, and service in industrial and hospital environments, many researchers have decided to conduct research in this field and route planning. The main challenge is to find a short route with a lack of collision with obstacles. This study examines path design for mobile robots and proposes a new and efficient idea for routing. Besides the short distance of the route and lack of collision with obstacles, the proposed method investigates other factors such as the safe distance from obstacles, path smoothness, and multiple robots. The results show the superior precision and speed of the proposed algorithm compared to similar algorithms. The suggested approach finds the shortest path with a safe distance from obstacles, in a minimum time. The major contributions of this method are summarized below: (1) a biogeographical algorithm is formulated for robot routing. (2) To improve the basic biogeographical algorithm, basic operations of the particle swarm optimization and genetic algorithm are integrated with it. (3) In addition to the shortest path problem, other problems such as path smoothness with a new idea and the safe distance from obstacles are included. Path smoothing is performed without involving it in the cost function, and merely through interpolation of the points found by the algorithm. (4) The proposed algorithm results in a good efficiency and finds the appropriate solution in a few iterations.
DOI
10.1007/s12652-023-04565-1
Cilt
14
