摘要
根据变电站巡检机器人的巡检环境和巡检任务,提出采用栅格法模拟划分机器人的工作空间,将变电站工作环境分解成一系列具有二值信息的网格单元,并结合遗传算法对变电站巡检机器人进行全局路径规划。提出了连续相邻栅格定义和不等长染色体编码,并使用自适应方法选取了交叉概率和变异概率进行路径寻优。通过MATLAB仿真,证明了这种栅格地图与遗传算法结合的方法能快速、有效地在已知环境中得到机器人的避障最优路径。
According to the inspection environment and inspection tasks substation inspection robot, the proposed division of the robot using the grid method simulation workspace environment will break down into a series of substation grid cell has a binary information, combined with genetic algorithm substation inspection robot global path planning. Proposed continuous adjacent grid definition and unequal chromosome coding and adaptive method selected crossover probability and mutation probability path optimization. By MATLAB simulation proved that the grid map and genetic algorithm combined method can quickly and effectively get optimal path obstacle avoidance robot in a known environment.
出处
《科技与创新》
2015年第6期12-14,共3页
Science and Technology & Innovation
基金
上海市电站自动化技术重点实验室项目(编号:13DZ2273800)
关键词
巡检机器人
栅格法
改进遗传算法
路径规划
inspection robot
grid method
improved genetic algorithm
path planning
