Harmony search based algorithm for mobile robot global path planning

Panov, Stojanche; Koceski, Saso

doi:10.1109/meco.2013.6601347

Cited by 3 publications

(4 citation statements)

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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%

“…where Xi is the set of possible values in range [1;maximumNumberOfRectangles], which means all possible values are dependent on the number of rectangles generated by quad-tree, denoted as maximumNumberOfRectangles. The equation states that, with a probability of HMCR, a candidate solution xi' will be generated from the HM, and with a probability of (1-HMCR) it will be generated randomly from the set of possible values Xi.…”

Section: Quad Harmony Search (Qhs) Algorithm Descriptionmentioning

confidence: 99%

“…Although it has not always been possible to find an optimal path in grid-based environments using such algorithms, these researches have served as a great example and a catalyst for finding alternatives to existing algorithms, thus providing either better time or memory complexities - key points of exploration to be seriously considered. Such research proved that these algorithms obtain poor results and a lack optimality when they have either very high or very low occupancy with obstacles in the working environment [1].…”

Section: Introductionmentioning

confidence: 99%

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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%

Section: Quad Harmony Search (Qhs) Algorithm Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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“…In [9], a method for global path planning was presented using the DE algorithm and the Voronoi diagram for modeling the environment. In 2012, Jati et al [10] introduced a hybrid mix of harmony search (HS) and bacterial foraging (BF) for multi-robot path planning. The proposed method inserts the chemo-tactic behavior of BF into the state of the HS for better stability.…”

Section: Introductionmentioning

confidence: 99%

Experimental study of path planning problem using EMCOA for a holonomic mobile robot

Alireza¹,

Duchaine²,

Tony³

2021

J. of Syst. Eng. Electron.

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In this paper, a comparative study of the path planning problem using evolutionary algorithms, in comparison with classical methods such as the algorithm, is presented for a holonomic mobile robot. The configured navigation system, which consists of the integration of sensors sources, map formatting, global and local path planners, and the base controller, aims to enable the robot to follow the shortest smooth path delicately. Grid-based mapping is used for scoring paths efficiently, allowing the determination of collision-free trajectories from the initial to the target position. This work considers the evolutionary algorithms, the mutated cuckoo optimization algorithm (MCOA) and the genetic algorithm (GA), as a global planner to find the shortest safe path among others. A non-uniform motion coefficient is introduced for MCOA in order to increase the performance of this algorithm. A series of experiments are accomplished and analyzed to confirm the performance of the global planner implemented on a holonomic mobile robot. The results of the experiments show the capacity of the planner framework with respect to the path planning problem under various obstacle layouts.

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