The Mixing Algorithm of ACO and GA Based Global Path Planning Method for Mobile Robot
| Autor: | Jiang Lei Dong, Shi Gang Cui, Fan Liang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Mathematical optimization
Meta-optimization Heuristic business.industry Computer science Heuristic (computer science) Ant colony optimization algorithms Population-based incremental learning Crossover MathematicsofComputing_NUMERICALANALYSIS General Medicine ComputingMethodologies_ARTIFICIALINTELLIGENCE Genetic algorithm Combinatorial optimization Pheromone Artificial intelligence Motion planning business Metaheuristic Algorithm |
| Zdroj: | Applied Mechanics and Materials. :1290-1293 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.494-495.1290 |
| Popis: | An ant colony algorithm is a stochastic searching optimization algorithm that is based on the heuristic behavior of the biologic colony. Its positive feedback and coordination make it possible to be applied to a distributed system. It has favorable adaptability in solving combinatorial optimization and has great development potential for its connotative parallel property. This study focused on global path planning with an ant colony algorithm in an environment based on grids, which explores a new path planning algorithm. How to present and update the pheromone of an ant system was investigated. The crossover operation of a genetic algorithm was used in the ant system for path optimization. Experimental results show that the algorithm has better path planning optimization ability than other algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|