Global Path Planning in Grid-Based Environments Using Novel Metaheuristic Algorithm

Panov, Stojanche; Koceska, Nataša

doi:10.1007/978-3-319-01466-1_11

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…In this paper, we introduce a novel approach, based on the utilization of the HS algorithm, to the problem of graph search in grid-based environments [1, 33]. The grids that have been examined are of a rectangular shape, having square-sized cells of fixed height and width, and the agent was able to move in four directions, marked as north (N), east (E), south (S) and west (W).…”

Section: Quad Harmony Search (Qhs) Algorithm Descriptionmentioning

confidence: 99%

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

Koceski

Panov

Koceska

et al. 2014

International Journal of Advanced Robotic Systems

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A novel approach to the problem of grid-based path finding has been introduced. The method is a blockbased search algorithm, founded on the bases of two algorithms, namely the quad-tree algorithm, which offered a great opportunity for decreasing the time needed to compute the solution, and the harmony search (HS) algorithm, a meta-heuristic algorithm used to obtain the optimal solution. This quad HS algorithm uses the quad-tree decomposition of free space in the grid to mark the free areas and treat them as a single node, which greatly improves the execution. The results of the quad HS algorithm have been compared to other metaheuristic algorithms, i.e., ant colony, genetic algorithm, particle swarm optimization and simulated annealing, and it was proved to obtain the best results in terms of time and giving the optimal path.

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Section: Quad Harmony Search (Qhs) Algorithm Descriptionmentioning

confidence: 99%

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

Koceski

Panov

Koceska

et al. 2014

International Journal of Advanced Robotic Systems

Self Cite

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Locomotion Planning for Quadruped Robot Walking on Lunar Rough Terrain

Chu

Zhang

Zhou

et al. 2022

Adv. Astronaut. Sci. Technol.

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A Cooperative Switching Algorithm for Multi-Agent Foraging

Zedadra

Séridi

Jouandeau

et al. 2016

Engineering Applications of Artificial Intelligence

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Foraging is the act of searching for, and when found transporting objects to one or more sinks. Although foraging can be accomplished by one single robot operating individually, it can be supported more efficiently by multiple robots operating collectively. The efficiency of the group of robots can be sufficiently improved through coordination. Pheromone-based communication is well suited for the coordination of swarm of robots. It is one of the main subjects of swarm intelligence that provides intelligent global behaviors from simple local behaviors. The goal of this work, is to study the benefit of collective foraging via the implicit recruitment when one agent alerts the others to the location of food. We present therefore, a multi-agent foraging algorithm named Cooperative Switching Algorithm for Foraging (C-SAF) inspired from the classical ant system, where agents use pheromone to collectively search and avoid already visited cells, and to communicate the food location. C-SAF provides a quick search, optimal paths to return to nest and quick exploitation of food. We then generalize the algorithm to produce a flexible and extensible framework for foraging, that can be reused or extended by other foraging algorithms. A qualitative comparison with some related search and foraging algorithms is presented in this paper. A quantitative comparison shows that our algorithm outperforms the reference c-marking algorithm across a range of scenarios that differ in terms of agent, environment and food parameters.

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Global Path Planning in Grid-Based Environments Using Novel Metaheuristic Algorithm

Cited by 4 publications

References 13 publications

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

Locomotion Planning for Quadruped Robot Walking on Lunar Rough Terrain

A Cooperative Switching Algorithm for Multi-Agent Foraging

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