Dynamic Path Planning for Mobile Robot Based on Genetic Algorithm in Unknown Environment
In this paper, a dynamic path planning scheme based on genetic algorithm (GA) is presented for navigation and obstacle avoidance of mobile robot under unknown environment. The real coding, fitness function and specific genetic operators are devised in the algorithm. The unique coding technique decreases the conventional computational complexity of genetic algorithm. It also speeds up the execution of searching by projecting two dimensional data to one dimensional data, which reduce the size of search space. The fitness function of genetic algorithm takes full consideration of three factors: the collision avoidance path, the shortest distance and smoothness of the path. The specific genetic operators are also selected to make the genetic algorithm more effective. The simulation experiments are made under the VC++ 6.0 environment. The simulation results verify that the genetic algorithm is high effective under various complex dynamic environments.
Dynamic Path Planning Mobile Robot Genetic Algorithm Obstacle Avoidance Unknown environment
Pu Shi Yujie Cui
Department of Automation Engineering, Northeastern University, Qinhuangdao, 066004, China
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
4325-4329
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）