An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots

作者：Qu, Hong^*; Xing, Ke; Alexander, Takacs

来源：Neurocomputing, 2013, 120: 509-517.

DOI：10.1016/j.neucom.2013.04.020

• Genetic Algorithm (GA)
• Co-evolution
• Co-evolutionary Improved Genetic Algorithm (CIGA)
• Global path planning
• Multiple robots

This paper presents a Co-evolutionary Improved Genetic Algorithm (CIGA) for global path planning of multiple mobile robots, which employs a co-evolution mechanism together with an improved genetic algorithm (GA). This improved GA presents an effective and accurate fitness function, improves genetic operators of conventional genetic algorithms and proposes a new genetic modification operator. Moreover, the improved GA, compared with conventional GAs, is better at avoiding the problem of local optimum and has an accelerated convergence rate. The use of a co-evolution mechanism takes into full account the cooperation between populations, which avoids collision between mobile robots and is conductive for each mobile robot to obtain an optimal or near-optimal collision-free path. Simulations are carried out to demonstrate the efficiency of the improved GA and the effectiveness of CIGA.

• 出版日期2013-11-23
• 单位电子科技大学