vector<double>&local_x,vector<double>&local_y,vector<double> &local_yaw,int local_point_id) { //double yaw_change=azimuthAngle(x_orignal[local_point_id+keep_point],y_orignal[local_point_id+keep_point], //x_target[local_point_id+keep_point+chang_lane_point],y_target[local_point_id+keep_point+chang_lane_point]); double dx=x_target[local_point_id+keep_point+chang_lane_point]-x_orignal[local_point_id+keep_point]; // keep_point--生成局部路径前的保持距离 double dy=y_target[local_point_id+keep_point+chang_lane_point]-y_orignal[local_point_id+keep_point]; Eigen::Matrix3d axis_rotation; axis_rotation = Eigen::AngleAxisd(yaw_orignal[local_point_id+keep_point], Eigen::Vector3d::UnitZ()) * Eigen::AngleAxisd(0, Eigen::Vector3d::UnitY()) * Eigen::AngleAxisd(0, Eigen::Vector3d::UnitX()); Eigen::Vector3d local_axis_loc(dx, dy, 0); auto local_axis_point=axis_rotation.inverse()*local_axis_loc; double local_angle=abs(atan((local_axis_point[0])/(local_axis_point[1]))); double xxx=local_axis_point[0]; double yyy=local_axis_point[1]; double x_average=local_axis_point[0]/(chang_lane_point+1); if (local_angle>M_PI_2) local_angle=M_PI-local_angle; else if (local_angle<-M_PI_2) local_angle=M_PI+local_angle; double change_rate_angle=(M_PI_2-local_angle)/(chang_lane_point+1)*2; if(x_target[local_point_id+keep_point+chang_lane_point]-x_orignal[local_point_id+keep_point]==0) { return false; }
时间: 2023-09-12 19:12:21 浏览: 145
这段代码是一个函数,接受一些参数并返回一个布尔值。函数的目的似乎是计算一些局部路径相关的值。在代码中,它首先计算了一些坐标和角度的差异,并使用旋转矩阵将坐标转换到局部坐标系中。然后,它计算了一些角度和变化率,并根据一些条件确定了最终的局部角度值。最后,它检查一些条件并返回一个布尔值。
需要注意的是,代码中的一行 `return false;` 是不符合函数的返回类型的,因为函数被声明为返回一个引用。这可能是一个错误或者需要对代码进行额外的修改。
相关问题
win10 下如何安装########## <?xml version="1.0"?> <package format="3"> <name>trac_ik_lib</name> <version>1.6.6</version> <description> TRAC-IK is a faster, significantly more reliable drop-in replacement for KDL's pseudoinverse Jacobian solver. The TRAC-IK library has a very similar API to KDL's IK solver calls, except that the user passes a maximum time instead of a maximum number of search iterations. Additionally, TRAC-IK allows for error tolerances to be set independently for each Cartesian dimension (x,y,z,roll,pitch.yaw). </description> <author>Patrick Beeson</author> <author>Barrett Ames</author> <maintainer email="robotics@traclabs.com">TRACLabs Robotics</maintainer> <license>BSD</license> <buildtool_depend>catkin</buildtool_depend> <build_depend>boost</build_depend> <build_depend>cmake_modules</build_depend> <build_depend>eigen</build_depend> <build_depend>kdl_parser</build_depend> <build_depend>libnlopt-dev</build_depend> <build_depend condition="$ROS_DISTRO == noetic">libnlopt-cxx-dev</build_depend> <build_depend>pkg-config</build_depend> <build_depend>roscpp</build_depend> <build_depend>urdf</build_depend> <build_export_depend condition="$ROS_DISTRO == noetic">libnlopt-cxx-dev</build_export_depend> <exec_depend>boost</exec_depend> <exec_depend>kdl_parser</exec_depend> <exec_depend>libnlopt-dev</exec_depend> <exec_depend>libnlopt0</exec_depend> <exec_depend>roscpp</exec_depend> <exec_depend>urdf</exec_depend> </package>
这是一个 ROS 包的描述文件,需要使用 ROS 环境来安装和使用。
在 Win10 上安装 ROS 可以参考以下步骤:
1. 安装虚拟机软件,例如 VMware Workstation 或 VirtualBox。
2. 下载 Ubuntu 镜像,可以从 Ubuntu 官网下载。
3. 创建一个新的虚拟机,将 Ubuntu 镜像作为虚拟机的启动盘。
4. 启动虚拟机,按照 Ubuntu 的安装向导进行安装。
5. 在 Ubuntu 中安装 ROS,可以参考 ROS 官方文档中的安装指南。
6. 下载 trac_ik_lib 包,将包放置在 ROS 工作空间的 src 目录中。
7. 在 ROS 工作空间的根目录中,运行以下命令编译 trac_ik_lib 包:
```
catkin_make
```
8. 运行以下命令激活 ROS 环境:
```
source devel/setup.bash
```
9. 运行以下命令启动 trac_ik_lib:
```
roslaunch trac_ik_lib trac_ik.launch
```
这些步骤完成后,trac_ik_lib 就可以在 Win10 上使用了。
if(local_point_id+keep_point+chang_lane_point<x_orignal.size()) { local_x.assign(x_orignal.begin()+local_point_id,x_orignal.begin()+local_point_id+keep_point+1); local_y.assign(y_orignal.begin()+local_point_id,y_orignal.begin()+local_point_id+keep_point+1); local_yaw.assign(yaw_orignal.begin()+local_point_id,yaw_orignal.begin()+local_point_id+keep_point); for (unsigned int i = 0; i < int(chang_lane_point/2); i++) { double local_xx=(i+1)*abs(x_average); double local_yy=(local_axis_point[1]/abs(local_axis_point[1]))*(i+1)*abs(x_average) * tan(change_rate_angle*(i+1)); local_x.push_back(local_xx*cos(yaw_orignal[local_point_id+keep_point])-local_yy*sin(yaw_orignal[local_point_id+keep_point])+x_orignal[local_point_id+keep_point]); local_y.push_back(local_xx*sin(yaw_orignal[local_point_id+keep_point])+local_yy*cos(yaw_orignal[local_point_id+keep_point])+y_orignal[local_point_id+keep_point]); local_yaw.push_back(change_rate_angle*(i+1)); } local_x.push_back(local_axis_point[0]/2*cos(yaw_orignal[local_point_id+keep_point])-local_axis_point[1]/2*sin(yaw_orignal[local_point_id+keep_point])+x_orignal[local_point_id+keep_point] ); local_y.push_back(local_axis_point[0]/2*sin(yaw_orignal[local_point_id+keep_point])+local_axis_point[1]/2*cos(yaw_orignal[local_point_id+keep_point])+y_orignal[local_point_id+keep_point] ); local_yaw.push_back(change_rate_angle*12); for (unsigned int i = 0; i < int(chang_lane_point/2); i++) { double local_xx_2=local_axis_point[0]-(int(chang_lane_point/2)-i)*abs(x_average); double local_yy_2=local_axis_point[1]-(local_axis_point[1]/abs(local_axis_point[1]))*(int(chang_lane_point/2)-i)*abs(x_average) * tan((change_rate_angle*(int(chang_lane_point/2)-i))); local_x.push_back(local_xx_2*cos(yaw_orignal[local_point_id+keep_point] )-local_yy_2*sin(yaw_orignal[local_point_id+keep_point] )+x_orignal[local_point_id+keep_point]); local_y.push_back(local_xx_2*sin(yaw_orignal[local_point_id+keep_point] )+local_yy_2*cos(yaw_orignal[local_point_id+keep_point] )+y_orignal[local_point_id+keep_point]); local_yaw.push_back(change_rate_angle*(int(chang_lane_point/2)-i)); } if(keep_point+chang_lane_point<local_path_size) { local_x.insert(local_x.end(),x_target.begin()+local_point_id+keep_point+chang_lane_point,x_target.begin()+(local_path_size+local_point_id-1)); local_y.insert(local_y.end(),y_target.begin()+local_point_id+keep_point+chang_lane_point,y_target.begin()+(local_path_size+local_point_id-1)); local_yaw.insert(local_yaw.end(),yaw_orignal.begin()+local_point_id+keep_point+chang_lane_point,yaw_orignal.begin()+(local_path_size+local_point_id-1)); } else { cout<<"keep_point + chang_lane_point 大于"<<local_path_size<<endl; }
这段代码是在给定一些条件的情况下,将一些值添加到 `local_x`、`local_y` 和 `local_yaw` 向量中的过程。首先,它检查 `local_point_id+keep_point+chang_lane_point` 是否小于 `x_orignal` 向量的大小。如果是,则将一些值从 `x_orignal`、`y_orignal` 和 `yaw_orignal` 向量中复制到 `local_x`、`local_y` 和 `local_yaw` 向量中。接下来,它使用一些循环和计算来计算一些局部路径点的坐标和角度,并将它们添加到 `local_x`、`local_y` 和 `local_yaw` 向量中。最后,如果满足条件 `keep_point+chang_lane_point<local_path_size`,则将一些额外的值从 `x_target`、`y_target` 和 `yaw_orignal` 向量中添加到 `local_x`、`local_y` 和 `local_yaw` 向量中。否则,输出一条错误消息。
需要注意的是,代码中的一些计算和索引操作可能需要进一步检查和验证,以确保其正确性和边界情况的处理。同时,代码中的输出语句 `cout<<"keep_point + chang_lane_point 大于"<<local_path_size<<endl;` 可能需要根据实际需求进行修改或处理。
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