Optimised path planning using Enhanced Firefly Algorithm for a mobile robot

• Published in: PloS one Vol. 19; no. 8; p. e0308264
• Main Authors: Ab Wahab, Mohd Nadhir, Nazir, Amril, Khalil, Ashraf, Bhatt, Benjamin, Mohd Noor, Mohd Halim, Akbar, Muhammad Firdaus, Mohamed, Ahmad Sufril Azlan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 12.08.2024; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Autonomous vehicles; Civil engineering; Clustering; Collision avoidance; Computer and Information Sciences; Computer science; Construction costs; Cost control; Deep learning; Design and construction; Efficiency; Energy consumption; Engineering and Technology; Feature selection; Heuristic; Heuristic methods; Machine learning; Mobile robots; Neural networks; Optimization; Parameter modification; Path planning; Physical Sciences; Position (location); Research and Analysis Methods; Robotics; Robotics - methods; Robots; Malaysia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0308264

Path planning is a crucial element of mobile robotics applications, attracting considerable interest from academics. This paper presents a path-planning approach that utilises the Enhanced Firefly Algorithm (EFA), a new meta-heuristic technique. The Enhanced Firefly Algorithm (FA) differs from the ordinary FA by incorporating a linear reduction in the α parameter. This modification successfully resolves the constraints of the normal FA. The research involves experiments on three separate maps, using the regular FA and the suggested Enhanced FA in 20 different runs for each map. The evaluation criteria encompass the algorithms’ ability to move from the initial location to the final position without experiencing any collisions. The assessment of path quality relies on elements such as the distance of the path and the algorithms’ ability to converge and discover optimum solutions. The results demonstrate significant improvements made by the Enhanced FA, with a 10.270% increase in the shortest collision-free path for Map 1, a 0.371% increase for Map 2, and a 0.163% increase for Map 3, compared to the regular FA. This work highlights the effectiveness of the Enhanced Firefly Algorithm in optimising path planning for mobile robotics applications, providing potential improvements in navigation efficiency and collision avoidance.