This project forked from zhaokun506/parking
自动泊车算法 混合A* 障碍物约束转化为行车走廊约束的优化与 apollo TDR-OBCA的比较
License: MIT License
此程序用于学习自动泊车，主要使用混合A*算法和数值优化的方法做自动停车
程序目前只关注一个周期的轨迹规划
1.参考apllo的混合A*算法生成初始路径
2.根据行车隧道**编写行车隧道算法
3.利用IPOPT 和ADOLC对优化问题进行求解
4.所有的数据通过matplotcpp进行图形绘制
5.程序经过初步调试，测试结果如下图所示：
202201107
1.增加了apollo TDR-OBCA算法测试对比。
2.增加了速度优化方法，使用了分段加加速度的优化方法
有待进一步研究： 1.详细的参数对比，包括运行效率，速度平滑性，控制平滑性，完成时间等 2.离散点的时间分配问题 3.搭建ros的测试环境，封装为ros包，以增强其通用性 4.参数对曲线的影响有待进行调参测试 5.此方法是将对混合A*的所有点进行优化，需要对采用关键路标点，点与点之间使用曲线连接，对曲线优化的方法进行研究对比。
参考借鉴： 百度apollo 湖南大学李柏《自动驾驶决策规划技术理论与实践》 浙江大学高飞移动机器人运动规划的知识 声明：仅仅作为个人学习使用
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