CAJ | 학술논문

在移动机器人路径规划问题中，环境建模约束定义难，遗传算法求解易陷入局部收敛，针对上述问题通过建立栅格坐标、栅格序号和栅格状态三者之间的关系，简化了障碍物约束和有效路径判断，同时引入多样性保持较好的元胞遗传算法，使用定长实数编码对生成的路径进行优化。仿真实验表明，由于算法具备较好的隐性迁移机制，保持了解的多样性，提高了算法收敛效率，使移动机器人路径规划问题得到了有效解决。
재이동궤기인로경규화문제중，배경건모약속정의난，유전산법구해역함입국부수렴，침대상술문제통과건립책격좌표、책격서호화책격상태삼자지간적관계，간화료장애물약속화유효로경판단，동시인입다양성보지교호적원포유전산법，사용정장실수편마대생성적로경진행우화。방진실험표명，유우산법구비교호적은성천이궤제，보지료해적다양성，제고료산법수렴효솔，사이동궤기인로경규화문제득도료유효해결。
When solving the problem of path planning of a mobile robot,defining constrains in environment modeling was hard, and was easily fallen into the local convergence by traditional genetic algorithm. By aimed at the problem above,and established the re-lationship among grid coordinates,grid number and grid state,the constrains definition of obstacles and effective path judging were simplified,at the same time,the cellular genetic algorithm with better diversity maintaining was also brought in,while optimizing the path by using fixed-length real number encoding. Finally,the simulation results show that the algorithm maintains the better diversity and improves the efficiency of the convergence because of the implicit mechanism of migration of the algorithm,which effectively solves the problem of path planning of the mobile robot.