Path planning for a mobile robot using genetic algorithms

Nagib, Gihan; Gharieb, W.

doi:10.1109/iceec.2004.1374415

Cited by 46 publications

(31 citation statements)

References 7 publications

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“…In [3], the region is represented as a graph of nodes, edges, and obstacles. In other words, the map is preprocessed and possible control points, where the route is allowed to pass, are determined.…”

Section: Related Workmentioning

confidence: 99%

Genetic Algorithms with Random Coordinates for Route Planning on a 3D Terrain

Özdikiş

2011

2011 Fifth International Conference on Genetic and Evolutionary Computing

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In this paper, an approach using genetic algorithms (GA) is proposed to find a feasible and optimum route on a 3D Geographical Information System (GIS) platform. The approach is based on generating random coordinates on the region instead of using discrete grids. Specialized crossover and mutation operators are defined accordingly. The feasibility criterion is to prevent the route from passing through the water. The two criteria to be optimized are the distance of the route from starting point to the destination point and the amount of climb ups/downs through the route. Our method is tested on NASA's World Wind application, which is an open source 3D virtual globe developed in Java.

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Section: Related Workmentioning

confidence: 99%

Genetic Algorithms with Random Coordinates for Route Planning on a 3D Terrain

Özdikiş

2011

2011 Fifth International Conference on Genetic and Evolutionary Computing

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“…In many occasions, researches use fixed-length chromosome to represent a path 33,34 . While in other circumstances, variable-length chromosomes are adopted.…”

Section: Ga-based Path Planningmentioning

confidence: 99%

Optimal Robot Path Planning for Multiple Goals Visiting Based on Tailored Genetic Algorithm

Liu¹,

Liang²,

Xian³

2014

IJCIS

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In real applications, mobile robot may be commanded to go to multiple goals to execute special commissions. This study analyzes the particular properties of this multiple goals visiting task and proposes a novel tailored genetic algorithm for optimal path planning for this task. In proposed algorithm, objectives for evaluating the path are energy consumption and idle time that are proposed in our previous work. Under the constraint of energy consumption, it will generate an optimal path that comprises as more goals as possible and as less idle time as possible. In this algorithm, customized chromosome representing a path and genetic operators including Repair, Cut and Deletion are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.

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“…The distance of a path indicated by the chromosome is used to find its fitness, since fitness should increase as distance decreases. Thus, the fitness function (F) of a feasible path is evaluated (Nagib and Gharieb, 2004). …”

Section: Genetic Algorithm Techniquementioning

confidence: 99%

Controlling the Motion of an Autonomous Mobile Robot Using Various Techniques: a Review

Mohanty¹,

Parhi²

2013

JAME

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Autonomous navigation of mobile robots in an uncertain and complex environment is a broad and complicated issue due to a variety of obstacles that mobile robots have to detect and represent in their maps to navigate safely. The objective of the navigation-mobile robot is to obtain an optimum path, meaning that the robot should plan a reliable path between the source point and the target point without colliding with the static and dynamic obstacles found in an uncertain and complex environment. Several efficient techniques have been developed by researchers in the motion planning of mobile robots. This paper presents detailed analysis of various techniques used in the autonomous navigation of mobile robot.

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Path planning for a mobile robot using genetic algorithms

Cited by 46 publications

References 7 publications

Genetic Algorithms with Random Coordinates for Route Planning on a 3D Terrain

Genetic Algorithms with Random Coordinates for Route Planning on a 3D Terrain

Optimal Robot Path Planning for Multiple Goals Visiting Based on Tailored Genetic Algorithm

Controlling the Motion of an Autonomous Mobile Robot Using Various Techniques: a Review

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