2012 IEEE Congress on Evolutionary Computation 2012
DOI: 10.1109/cec.2012.6256142
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Abstract: Path planning is a critical combinatorial problem essential for the navigation of a mobile robot. Several re search initiatives, aiming at providing optimized solutions to this problem, have emerged. Ant Colony Optimization (ACO) and Genetic Algorithms (GA) are the two most widely used heuristics that have shown their effectiveness in solving such a problem. This paper presents, smartPATH, a new hybrid ACO GA algorithm to solve the global robot path planning problem. The algorithm consists of a combination of … Show more

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Cited by 54 publications
(52 citation statements)
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References 17 publications
(17 reference statements)
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“…The first ACO algorithm, called Ant System (AS), was applied to the Traveling Salesman Problem (TSP) by Dorigo M. [1]. It constitutes the main framework of other ACO algorithms and is considered as a prototype.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…The first ACO algorithm, called Ant System (AS), was applied to the Traveling Salesman Problem (TSP) by Dorigo M. [1]. It constitutes the main framework of other ACO algorithms and is considered as a prototype.…”
Section: Related Workmentioning
confidence: 99%
“…And robotic is gaining a lot of interest in our daily life and in several areas including industrial applications, manufacturing and constructions, search, rescue, environment exploration and others [1]. Mobile robots path planning is a critical and fundamental problem in the field of mobile robots, whose main task is finding a collision-free path for the robot starting from its initial location to the target location in a given environment with obstacles while satisfy a set of optimization criteria including traveled distance, processing time and energy consumption.…”
Section: Introductionmentioning
confidence: 99%
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“…The grid-map is divided into cells in which the robot has to traverse a set of free cells to reach its goal. In the literature, several heuristic solutions and approaches have been proposed to solve the global path planning problem such as Ant Colony Optimization (ACO) (Chaari et al 2012), Genetic Algorithms (GA) (Alajlan et al 2013), Particle Swarm Optimization (PSO) (Shiltagh and Jalal 2013) and Tabu Search (TS) (Masehian and Amin-Naseri 2006). Other techniques are based on exact methods, such as Dijkstra and A*, which have the advantage of being complete and guarantee finding the optimal solution if it exists.…”
Section: Introductionmentioning
confidence: 99%
“…The path finding problem is typically defined in terms of the Travelling Salesman Problem (TSP) [7] or a more general Vehicle Routing Problem (VRP) [4]. Determining the optimal solution is an NP-hard problem, so the size of problems that can be solved optimally is limited [3]. In the situation of environment monitoring systems, the problem is even more complex because exact positions of the sampling points are not known a priori.…”
Section: Introductionmentioning
confidence: 99%