教育用路径可规划智能车研发
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摘要
针对高中科技社团和大学计算机相关专业科技创新教育需求,开发一种可以用于电子和计算机科技教学的智能小车。智能小车在完成路径规划后,可以按照规划的路径完成任务;还可以设定目标点与障碍点,智能小车基于改进的Dijkstra算法自动搜索到达终点的最优路径。除了培养学生电子设计能力,通过智能小车编程实践,也训练了学生对优化算法的学习。首先,采用微软基础类MFC与Matlab混合编程编写上位机界面,调用改进的Dijkstra算法进行路径规划。然后,将规划好的路径通过串口传到下位机,由STM32控制执行。最后,在栅格地图中,通过仿真运行和实际应用验证了改进的Dijkstra算法的可行性,取得了较好的效果。
Aiming at the demand of science & technology club in high schools and college computer science innovation education in colleges, we developed a smart car which can be used in electronic and computer science and technology teaching to provide students with a platform to study smart cars and path optimization algorithms. The host computer system is developed by Visual C++ and calls the Matlab engine to run the genetic algorithm and A~* or other optimization algorithms, carrying out path planning for different tasks and controlling the smart car through the serial port. Through simulation and practical application, it is verified that in our interactive platform, different path planning algorithms designed by Matlab can be implemented to control the smart cars. When students want to study the path planning and then control the smart car, they only need to use Matlab to implement the path planning algorithm of the smart car, without designing a platform of interactive interface and a program of smart car controlling in addition.
Aiming at the demand of science & technology club in high schools and college computer science innovation education in colleges, we developed a smart car which can be used in electronic and computer science and technology teaching to provide students with a platform to study smart cars and path optimization algorithms. The host computer system is developed by Visual C++ and calls the Matlab engine to run the genetic algorithm and A~* or other optimization algorithms, carrying out path planning for different tasks and controlling the smart car through the serial port. Through simulation and practical application, it is verified that in our interactive platform, different path planning algorithms designed by Matlab can be implemented to control the smart cars. When students want to study the path planning and then control the smart car, they only need to use Matlab to implement the path planning algorithm of the smart car, without designing a platform of interactive interface and a program of smart car controlling in addition.
引文
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[2]陈平.辅助驾驶中控制与决策关键技术研究[D].上海交通大学,2011.
[3]DAI B,XIAO X M,CAI Z X.Current Status and Future Development of Mobile Robot Path Planning Technology[J].Control Engineering of China,2005,12(3):198-202.
[4]沈小伟.移动机器人路径规划研究[J].Engineering of China,2005,12(3):198-202.
[5]贾亚军.生物启发式算法及其改进研究[D].中国科学技术大学,2010.
[6]孙健,钟义信,王伟.利用遗传算法求解TSP(Travelling Salesman Problem)问题的探讨[C]//全国信息论与通信理论学术会议.2000.
[7]金希东.遗传算法及其应用[D].西南交通大学,1996.
[8]梁宇宏,张欣.对遗传算法的轮盘赌选择方式的改进[J].信息技术,2009,33(12):127-129.
[9]黄蓉,刘敏.基于A*算法求解最短路径的实现原理[J].企业家天地(下半月刊),2009(7):124-125.
[10]尹芳.一次路由计算实现层次路由的拓扑方法:CN,CN1816000 A[P].2006.
[11]任世军,洪炳镕,黄德海.一种基于栅格扩展的机器人路径规划方法[J].哈尔滨工业大学学报,2001,33(1):68-72.
[12]ZHAO Y L.Data structures and algorithms[M].Tsinghua University press,2008.
[13]刘金琨.先进PID控制MATLAB仿真[电子资源][M].电子工业出版社,2004