Computer Science

Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 97-100.

• Intelligent Computing • Previous Articles     Next Articles

PSO-ACO Fusion Algorithm Based on Optimal Path Planning in Indoor Environment

LIU Jun, XU Ping-ping, WU Gui-lu, PENG Jie   

  1. National Mobile Communications Laboratory,Southeast University,Nanjing 210096,China
  • Online:2019-02-26 Published:2019-02-26

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Abstract: In order to find the optimal path for mobile robot to reach the specified destination in indoor obstacle environment,an improved PSO-ACO fusion algorithm based on particle swarm optimization (PSO) and ant colony algorithm (ACO) was proposed.In PSO-ACO fusion algorithm,ant colony algorithm is used to obtain the global optimal solution for the local optimal problem caused by premature particle in particle swarm optimization algorithm.At that same time,the problem of small variety of particles in the PSO algorithm and lack of initialization pheromone and time consume in the ACO algorithm are effectively solved.Simulation results show that PSO-ACO fusion algorithm can greatly improve the ability of searching the optimal solution and realize the optimal path planning under the premise of improving the global search ability and search speed of the algorithm compared with particle swarm optimization and ant colony algorithm.

Key words: Ant colony algorithm, Indoor environment, Optimal path planning, Particle swarm optimization, PSO-ACO fusion algorithm

CLC Number: 

  • TP242.2
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