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

Abstract

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.

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

“…In this study, the authors claimed that both solutions provide very comparable results for small problem sizes, but when increasing the size and the complexity of the problem, the ACO-based algorithm produces a shorter path at the cost of a higher execution time, as compared to the GA-based algorithm. Four heuristic methods were compared in the study by Koceski et al 11 : ACO, particle swarm optimization ( PSO), GA and a new technique called quad harmony search ( QHS) that is a combination between the quad tree algorithm and the harmony search method. The quad tree method is used to decompose the grid map in order to accelerate the search process, and the harmony method is used to find the optimal path.…”

Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment

“…Developed from A-Star, D-Star can make dynamic path planning but the shortest path is still influenced by the density of grid [19]. In addition, Ant Colony (AC) needs grid to compute the matrix of pheromone concentration [20] and Genetic Algorithm (GA) needs grid to make genetic operation [21]. Both methods rely on infinite iterations to approach a theoretical optimum.…”

Inverse Kinematics Solution of a Robot Arm based on Adaptive Neuro Fuzzy Interface System

“…This is a result not only on the advancements in material design and their low prices but, also due to the development of novel control paradigms as well as development of Artificial Intelligence (AI). The growing popularity of the Artificial Intelligence (AI) and its application in various fields [1], starting from tourism [2], through medicine [3][4][5], biology [6], education [7], robotics [8][9][10][11], and also in economy [12], is mainly due to the apparatus i.e. the models and techniques used to mimic the human reasoning, learn and improve during time.…”