New Harmony Search Algorithm for Mobile Robot Path Planning

Quan, Yongbin; Wei, Wüchang; Ouyang, Haibin; Lan, Xuejing

doi:10.1007/978-981-15-8155-7_289

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…From the review of the available literature on intelligent path-planning techniques such as cell decomposition [5], fuzzy logic [6], neural network [7], particle swarm optimization algorithm [8], ant colony algorithm [9], bacterial foraging optimization [10], harmony search algorithm [11], cuckoo search algorithm [12], and dragonfly algorithm [13], it is clear that the applications of metaheuristic algorithms for solving mobile robot navigational problems are growing rapidly compared to heuristic algorithms due to their high-performance capabilities. The "randomization" and "local search" features of the metaheuristic algorithm are critical.…”

Section: Review Of Literaturementioning

confidence: 99%

Self-Directed Mobile Robot Navigation Based on Functional Firefly Algorithm (FFA)

Patle,

Patel,

Jha

et al. 2023

Eng

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This paper proposes an optimized mobile robot navigation strategy using a functional firefly algorithm (FFA) and choice function. This approach has two key advantages: first, the linear objective function performs efficiently with the single degree and finite-order polynomial time operation, and second, the cartesian constraint performs compactly with the chosen degree of freedom on the finite interval. This functional approach optimizes the size of operational parameters in context with key size, operation time, and a finite range of verification. The choice function achieves parameter order (size) reduction. The attraction characteristic of fireflies is represented by the choice function for optimizing the choice between low and high intensities of fireflies. In 2D and 3D environments, the proposed robot navigation performs well in an uncertain environment with static and dynamic obstacles. This efficiency includes the robot’s speed as determined by the choice function’s minimum path lengths. The collision-free path is achieved by the non-void family of non-void sets. The obtained results are optimal in terms of path length and navigational time. The proposed controller is also compared with the other existing controllers, and it is observed that the FFA gives the shortest path in less time for the same environmental condition.

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