lu750310的博客

自定义QML组件import QtQuick 2.12import QtQuick.Window 2.12import QtQuick.Controls 2.5import QtQuick.Controls 1.4 as Ctr1import QtQuick.Layouts 1.2import './Text.js' as JieWindow{ id:window width:640 height:480 visible: true title:".

https://www.liaoxuefeng.com/wiki/896043488029600/?ivk_sa=1024320u

void Path_tracking::multi_select(const PoseSE2& currant_odom_pose){int i=0,j=0;for(geometry_msgs::PoseStamped each_path_point:map_path.poses){geometry_msgs::PoseStamped path_point_odom;try{tf_listener.transformPose(“odom”, ros::Time(0),each_pat

<?xml version="1.0"?><robot name="mbot" xmlns:xacro="http://www.ros.org/wiki/xacro"> <!-- PROPERTY LIST --> <xacro:property name="M_PI" value="3.1415926"/> <xacro:property name="base_mass" value="20" /> &l

1.基本结构1.数组的建立numbers = np.array([1,2,3,4])#建立数组print(numbers)numbers.dtype类型输出[1 2 3 4]dtype('int32')#数组每个元素的类型都是一样的，int->float->char2.numpy索引取值，与列表一样例一vector = numpy.array([5,10,15,20])print(vector[0:3])输出[ 5 10 15]例二matrix = np.

1.先记录一下自己踏进去的坑1.首先是python的scipy对应的线性规划库不可以以二维数组作为参数，cvxpy的决策变量也最高为二维2.cvxpy库最好还是安装37版本，如何建立多环境并安装包在我的另一篇博客有介绍3.cvxpy,一定要用resluts=prob.solve(solver=cp.CPLEX)，另外那个GLPK_MI别用我也看不懂那个求解器好点赛题模型Objective function(1): Meet the minimum costConstraint cond

第二周pltplt.hist问题import numpy as npimport matplotlib.pyplot as pltnp.random.seed(0)mu ,sigma =100,20#均值和标准差a=np.random.normal(mu,sigma,size = 100)plt.hist(a,20,density=True,histtype= 'stepfilled',facecolor = 'b',alpha = 0.75)#normed=1已经失效，改为density=

#!/usr/bin/env python# -*- coding: utf-8 -*-import rospyfrom geometry_msgs.msg import Twistimport sys, select, termios, ttymsg = """Control mbot!---------------------------Moving around: u i o j k l m , .q/z : increas

修改hosts最后一行加（ip）自己查ip地址然后关掉