Comparative study of soft computing techniques for mobile robot navigation in an unknown environment

作者：

Highlights：

• Robot navigation and obstacle avoidance using fuzzy logic controller is presented.

• Soft computing techniques are used to optimize the performance of fuzzy logic.

• The automatic tuning was done by using three soft computing techniques: GA, PSO, and NN.

• The best performance in terms of travelling time and speed is based on GA-Fuzzy.

• The PSO-Fuzzy and Neuro-Fuzzy methods have better performance in terms of distance travelled.

摘要

•Robot navigation and obstacle avoidance using fuzzy logic controller is presented.•Soft computing techniques are used to optimize the performance of fuzzy logic.•The automatic tuning was done by using three soft computing techniques: GA, PSO, and NN.•The best performance in terms of travelling time and speed is based on GA-Fuzzy.•The PSO-Fuzzy and Neuro-Fuzzy methods have better performance in terms of distance travelled.

论文关键词：Mobile robot navigation,Soft computing,Fuzzy logic,Genetic algorithm,Particle swarm optimization,ANFIS

论文评审过程：Available online 10 April 2015.

论文官网地址：https://doi.org/10.1016/j.chb.2015.03.062