An Improved Genetic Algorithm for Mobile Robotic Path Planning
Proposed an improved genetic algorithm based on rough sets reduction theory, optimized the genetic operators, and overcame the weakness of the traditional genetic algorithm, such as huge number of initial population and slow velocity of optimization and convergence. The experiments both in simple and complex environment have been carried on. The simulation result indicated that the method can reduce the scale of the population, minimize the searching scope, and improve the velocity of the convergence and optimization for the mobile robotic path planning.
Mobile Robot Path Planning Rough Set Genetic Algorithm
Zhou Yongnian Zheng Lifang Li Yongping
Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, 201204, China The Grad Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, 201204, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
3267-3272
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）