CAJ | 학술논문

针对移动机器人路径规划的难题,运用了一种基于遗传模拟退火算法的移动机器人最优路径规划方法,对移动机器人的路径规划进行了设计,采用了栅格法对环境进行建模.为了提高路径规划的效率,采用了一种改进的避障算法来生成初始种群.将遗传算法与模拟退火算法相结合形成遗传模拟退火算法,新算法具有较强的全局和局部搜索能力.仿真实验结果证明算法相对于基本遗传算法的收敛速度、搜索质量和最优解输出概率方面有了明显的提高.
침대이동궤기인로경규화적난제,운용료일충기우유전모의퇴화산법적이동궤기인최우로경규화방법,대이동궤기인적로경규화진행료설계,채용료책격법대배경진행건모.위료제고로경규화적효솔,채용료일충개진적피장산법래생성초시충군.장유전산법여모의퇴화산법상결합형성유전모의퇴화산법,신산법구유교강적전국화국부수색능력.방진실험결과증명산법상대우기본유전산법적수렴속도、수색질량화최우해수출개솔방면유료명현적제고.
Aimed at the path planning problem of mobile robot, a genetically simulated annealing algorithm of optimum path planning for mobile robots is proposed. In this paper, path planning of mobile robot is designed, grid is used to make environmental modeling. An improved obstacle avoidance algorithm is introduced to generate the initial population in order to improve the path planning efficiency. This paper develops a genetic simulated annealing algo-rithm by combining the genetic algorithm with simulated annealing algorithm. The new algorithm has better capability of searching globally and locally. The simulation results demonstrate that the proposed algorithm has achieved consid-erable improvements, in convergence speed, search quality and optimal solution output rate compared to the basic ge-netic algorithm.