摘要
提出一种改进的量子进化算法来解决机器人实时路径规划问题。采用栅格法对环境建模,给出一种新型的解码方法来将量子个体转换为用栅格点表示的路径。在量子旋转门的基础上,引进遗传算法中的交叉和变异操作以及专门针对路径规划问题设计的修复算子,共同对量子种群进行更新,提升了算法的搜索效率。借助Matlab图形用户界面GUI实现对机器人实时路径规划过程的模拟,仿真结果表明,所提方法能够在较复杂的环境中规划出可行且长度较短的路径,且当环境中出现新的障碍物或原有障碍物向不同方向移动时,该方法均能及时地响应,重新规划出新的最优路径。
In order to solve the problem of real-time path planning for mobile robots, an improved quantum evolutionary algorithm was proposed. By using the grid method to build the environment model, a novel decoding method which transforms the quantum individual into the path described by grid points was presented. On the basis of the quantum ro- tation gate, the cross and mutation operator in genetic algorithm and a repair operation specifically designed for the path planning problem were introduced to update the quantum population together, which improved the searching efficiency. With the help of GUI in Matlab, process of the robot real-time path planning was simulated. Simulation results indicate that the proposed method can obtain a feasible and short path in the complex environment. Additionally, when a new ob- stacle appears suddenly, or the original ones move towards different directions, this method can also response quickly and replan an optimal path in the new environment.
出处
《计算机科学》
CSCD
北大核心
2013年第5期229-232,250,共5页
Computer Science
基金
江苏省高校自然科学研究计划项目(10KJB510010)
空间智能控制技术国家重点实验室项目
南京信息工程大学科研基金(20110393
20090211)资助
关键词
量子进化算法
实时路径规划
栅格法
GUI
Quantum evolutionary algorithm
Real-time path planning
Grid method
GUI
