20200427 win10 webots R2020a安装下载入门教程

目录

 

1.安装与修改语言

2.运行demo，了解功能

 3.创建简单的仿真

 5.添加激光雷达节点

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1.安装与修改语言

官网下载过慢

参考：https://blog.csdn.net/weixin_44504987/article/details/104753615

最新版Webots R2020a Windows版本软件下载链接 （百度网盘）提取码: hui1

双击安装

打开选择classic经典，其他的都关掉，不在提示。

 点击暂停，选择Tools->

 

英语改为汉语，点击yes，重启。

2.运行demo，了解功能

点击引导之旅

点击箭头，随便双击一个，如第一个，键盘上下左右控制运动

选取pioneer 3AT.wbt,此仿真以pioneer 3at为移动平台搭载激光雷达，进行运动控制。

 

 左侧1-2-3-4-5----是柱子

左侧如下图为车体，点击编辑即可编辑程序，不建议编辑，主要是了解整体的仿真流程

 3.创建简单的仿真

点击暂停，向导，新项目目录

 新世界，点击viewpoint，点击“加号”

 1.添加地面

添加机器人

设置地面大小和高度

车体，控制方式，点击选择，选择lidar，也可选择matlab，点击编辑即可进行程序编写

如果pioneer3at_obstacle_avoidance_with_lidar 需要添加Lidar传感器，不然会报如下错误，会一直向前走，无避障功能，新建机器人控制，将pioneer3at_obstacle_avoidance_with_lidar复制到新建的my_controler中

用户手册，点击help

 

 5.添加激光雷达节点

转化为节点，保存

参考：https://blog.csdn.net/crp997576280/article/details/105667450

 添加结构

 左键点击liodar，按住shift，点击绿色向上，可将其拖出来

 命名：Sick  291

 显示激光雷达

 改激光雷达的名字

/*
 * Copyright 1996-2019 Cyberbotics Ltd.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/*
 * Description:  Example of Sick LMS 291.
 *               The velocity of each wheel is set
 *               according to a Braitenberg-like algorithm which takes the values returned by the Sick as input.
 */

#include 
#include 
#include 
#include 
#include 
#include 

#define TIME_STEP 32
#define MAX_SPEED 6.4
#define CRUISING_SPEED 5.0
#define OBSTACLE_THRESHOLD 0.1
#define DECREASE_FACTOR 0.9
#define BACK_SLOWDOWN 0.9

// gaussian function
double gaussian(double x, double mu, double sigma) {
  return (1.0 / (sigma * sqrt(2.0 * M_PI))) * exp(-((x - mu) * (x - mu)) / (2 * sigma * sigma));
}

int main(int argc, char **argv) {
  // init webots stuff
  wb_robot_init();

  // get devices
  WbDeviceTag lms291 = wb_robot_get_device("Sick 291");
  WbDeviceTag front_left_wheel = wb_robot_get_device("front left wheel");
  WbDeviceTag front_right_wheel = wb_robot_get_device("front right wheel");
  WbDeviceTag back_left_wheel = wb_robot_get_device("back left wheel");
  WbDeviceTag back_right_wheel = wb_robot_get_device("back right wheel");

  // init lms291
  wb_lidar_enable(lms291, TIME_STEP);
  const int lms291_width = wb_lidar_get_horizontal_resolution(lms291);
  const int half_width = lms291_width / 2;
  const int max_range = wb_lidar_get_max_range(lms291);
  const double range_threshold = max_range / 20.0;
  const float *lms291_values = NULL;

  // init braitenberg coefficient
  double *const braitenberg_coefficients = (double *)malloc(sizeof(double) * lms291_width);
  int i, j;
  for (i = 0; i < lms291_width; ++i)
    braitenberg_coefficients[i] = gaussian(i, half_width, lms291_width / 5);

  // init motors
  wb_motor_set_position(front_left_wheel, INFINITY);
  wb_motor_set_position(front_right_wheel, INFINITY);
  wb_motor_set_position(back_left_wheel, INFINITY);
  wb_motor_set_position(back_right_wheel, INFINITY);

  // init speed for each wheel
  double back_left_speed = 0.0, back_right_speed = 0.0;
  double front_left_speed = 0.0, front_right_speed = 0.0;
  wb_motor_set_velocity(front_left_wheel, front_left_speed);
  wb_motor_set_velocity(front_right_wheel, front_right_speed);
  wb_motor_set_velocity(back_left_wheel, back_left_speed);
  wb_motor_set_velocity(back_right_wheel, back_right_speed);

  // init dynamic variables
  double left_obstacle = 0.0, right_obstacle = 0.0;

  // control loop
  while (wb_robot_step(TIME_STEP) != -1) {
    // get lidar values
    lms291_values = wb_lidar_get_range_image(lms291);
    // apply the braitenberg coefficients on the resulted values of the lms291
    // near obstacle sensed on the left side
    for (i = 0; i < half_width; ++i) {
      if (lms291_values[i] < range_threshold)  // far obstacles are ignored
        left_obstacle += braitenberg_coefficients[i] * (1.0 - lms291_values[i] / max_range);
      // near obstacle sensed on the right side
      j = lms291_width - i - 1;
      if (lms291_values[j] < range_threshold)
        right_obstacle += braitenberg_coefficients[i] * (1.0 - lms291_values[j] / max_range);
    }
    // overall front obstacle
    const double obstacle = left_obstacle + right_obstacle;
    // compute the speed according to the information on
    // obstacles
    if (obstacle > OBSTACLE_THRESHOLD) {
      const double speed_factor = (1.0 - DECREASE_FACTOR * obstacle) * MAX_SPEED / obstacle;
      front_left_speed = speed_factor * left_obstacle;
      front_right_speed = speed_factor * right_obstacle;
      back_left_speed = BACK_SLOWDOWN * front_left_speed;
      back_right_speed = BACK_SLOWDOWN * front_right_speed;
    } else {
      back_left_speed = CRUISING_SPEED;
      back_right_speed = CRUISING_SPEED;
      front_left_speed = CRUISING_SPEED;
      front_right_speed = CRUISING_SPEED;
    }
    // set actuators
    wb_motor_set_velocity(front_left_wheel, front_left_speed);
    wb_motor_set_velocity(front_right_wheel, front_right_speed);
    wb_motor_set_velocity(back_left_wheel, back_left_speed);
    wb_motor_set_velocity(back_right_wheel, back_right_speed);

    // reset dynamic variables to zero
    left_obstacle = 0.0;
    right_obstacle = 0.0;
  }

  free(braitenberg_coefficients);
  wb_robot_cleanup();

  return 0;
}

点击保存，生成

检测最大距离要够，避障阈值const double range_threshold = max_range / 20.0，要大于车体长度/2，不然转不过去

最后效果，灰色线是超声波模块/绿线是雷达，移动平台向前走，自主避障