ros sensor_msgs::laserscan 数据格式及velodyne_laserscan.cpp文件解析
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laserscan数据格式如下(摘自wiki):

每个成员都能根据注释轻松识别其功能和作用位置,在注释中明确指出容易产生误解的地方:ranges[]数组代表雷达旋转过程中记录的距离数据范围(从angle_min到angle_max),其大小并非固定为360个元素(取决于激光雷达的转速和方向角分辨率),即每隔多少角度采集一次数据(这正是消息中的angle_increment参数所决定的)。具体而言,在angle_min的角度对应的索引为0的位置开始存储数据;而intensities[]数组则与ranges[]对应地存储每个数据点的强度值或激光雷达的反射率信息。通过分析velodyne官方源码中的由pointCloud转为laserscan的文件velodyne_laserscan.cpp为例,在注释中详细说明如何发布laserscan消息。建议按照注释逐步阅读代码以理解其实现原理。
// Copyright (C) 2018, 2019 Kevin Hallenbeck, Joshua Whitley
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#include "velodyne_laserscan/velodyne_laserscan.h"
#include <sensor_msgs/point_cloud2_iterator.h>
namespace velodyne_laserscan
{
VelodyneLaserScan::VelodyneLaserScan(ros::NodeHandle &nh, ros::NodeHandle &nh_priv) :
nh_(nh), srv_(nh_priv), ring_count_(0)
{
ros::SubscriberStatusCallback connect_cb = boost::bind(&VelodyneLaserScan::connectCb, this);
// 注册并绑定收到pointcloud2消息的回调函数
pub_ = nh.advertise<sensor_msgs::LaserScan>("scan", 10, connect_cb, connect_cb);
//声明发布的话题
srv_.setCallback(boost::bind(&VelodyneLaserScan::reconfig, this, _1, _2));
//动态配置参数的回调函数,当设置的参数改变时回调调用
}
void VelodyneLaserScan::connectCb()
{
boost::lock_guard<boost::mutex> lock(connect_mutex_);
if (!pub_.getNumSubscribers())
{
sub_.shutdown();
}
else if (!sub_)
{
sub_ = nh_.subscribe("velodyne_points", 10, &VelodyneLaserScan::recvCallback, this);
}
}
//收到点云数据消息的回调实现,即转化数据并发布scan话题
void VelodyneLaserScan::recvCallback(const sensor_msgs::PointCloud2ConstPtr& msg)
{
// Latch ring count
// 一开始ring_count为零,有动态参数配置后或者第二次收到数据后,即可正常工作
// 此块逻辑不够清晰
if (!ring_count_)
{
// Check for PointCloud2 field 'ring'
// 检查点去数据中是否有激光ID值,如果没有,则此点云数据无效,不处理数据。
bool found = false;
for (size_t i = 0; i < msg->fields.size(); i++)
{
if (msg->fields[i].datatype == sensor_msgs::PointField::UINT16)
{
if (msg->fields[i].name == "ring")
{
found = true;
break;
}
}
}
if (!found)
{
ROS_ERROR("VelodyneLaserScan: Field 'ring' of type 'UINT16' not present in PointCloud2");
return;
}
//再次检查ring的值,感觉没鸟用,废代码
for (sensor_msgs::PointCloud2ConstIterator<uint16_t> it(*msg, "ring"); it != it.end(); ++it)
{
const uint16_t ring = *it;
if (ring + 1 > ring_count_)
{
ring_count_ = ring + 1;
}
}
if (ring_count_)
{
ROS_INFO("VelodyneLaserScan: Latched ring count of %u", ring_count_);
}
else
{
ROS_ERROR("VelodyneLaserScan: Field 'ring' of type 'UINT16' not present in PointCloud2");
return;
}
}
// Select ring to use
// 通过配置,获取需要抽取的激光ID,即需要取哪一条线(比如VLP16中抽第8号线)来发布scan,
// 并且给ring_count_赋值
uint16_t ring;
if ((cfg_.ring < 0) || (cfg_.ring >= ring_count_))
{
// Default to ring closest to being level for each known sensor
if (ring_count_ > 32)
{
ring = 57; // HDL-64E
}
else if (ring_count_ > 16)
{
ring = 23; // HDL-32E
}
else
{
ring = 8; // VLP-16
}
}
else
{
ring = cfg_.ring;
}
//如果没有配置参数,则按默认的线来运行,VLP16的8号laser id 最接近水平
ROS_INFO_ONCE("VelodyneLaserScan: Extracting ring %u", ring);
// Load structure of PointCloud2
//获取 PointCloud2 点云数据中x,y,z,强度,laserid的位置偏移,相当于数组索引
//初始值为-1,当获取到后,变为相应位置的正数,判断是否存在
int offset_x = -1;
int offset_y = -1;
int offset_z = -1;
int offset_i = -1;
int offset_r = -1;
for (size_t i = 0; i < msg->fields.size(); i++)
{
if (msg->fields[i].datatype == sensor_msgs::PointField::FLOAT32)
{
if (msg->fields[i].name == "x")
{
offset_x = msg->fields[i].offset;
}
else if (msg->fields[i].name == "y")
{
offset_y = msg->fields[i].offset;
}
else if (msg->fields[i].name == "z")
{
offset_z = msg->fields[i].offset;
}
else if (msg->fields[i].name == "intensity")
{
offset_i = msg->fields[i].offset;
}
}
else if (msg->fields[i].datatype == sensor_msgs::PointField::UINT16)
{
if (msg->fields[i].name == "ring")
{
offset_r = msg->fields[i].offset;
}
}
}
// Construct LaserScan message
// 是否存在x,y,z值,如果不存在就报错返回,如果存在就初始化/scan消息
// 初始化信息就可以看出/scan消息的结构组成
if ((offset_x >= 0) && (offset_y >= 0) && (offset_r >= 0))
{
// /scan 数据的精度,即range[]数组的大小,
// size 是一圈对应的精度,因为angle_min,angle_max 在后面已经固定写死了
// 因此size 是(pi-(-pi))/resolution
const float RESOLUTION = std::abs(cfg_.resolution);
const size_t SIZE = 2.0 * M_PI / RESOLUTION;
sensor_msgs::LaserScanPtr scan(new sensor_msgs::LaserScan());
scan->header = msg->header;
//可以看到angle_increment 的值即为RESOLUTION
scan->angle_increment = RESOLUTION;
//从-pi 到 pi ,程序已经写死了
scan->angle_min = -M_PI;
scan->angle_max = M_PI;
// 截取0 到 200 米范围的数据,已经超VLP16量程了,所有数据都有效
scan->range_min = 0.0;
scan->range_max = 200.0;
scan->time_increment = 0.0;
//按分辨率推出的,ranges的大小在此定义
scan->ranges.resize(SIZE, INFINITY);
// 标准的点云数据中各个数据的序号是有规律的,否则是不规则的数据
// 然而两者处理方式一样的,此处区分意义不大
if ((offset_x == 0) &&
(offset_y == 4) &&
(offset_i % 4 == 0) &&
(offset_r % 4 == 0))
{
scan->intensities.resize(SIZE);
const size_t X = 0;
const size_t Y = 1;
const size_t I = offset_i / 4;
const size_t R = offset_r / 4;
for (sensor_msgs::PointCloud2ConstIterator<float> it(*msg, "x"); it != it.end(); ++it)
{
const uint16_t r = *((const uint16_t*)(&it[R])); // ring
// 对比laser id 是否与需要取的一致,如果不一致,则不更新range[]以及intensities[]
if (r == ring)
{
const float x = it[X]; // x
const float y = it[Y]; // y
const float i = it[I]; // intensity
//求某一角度对应的序号,反正切值刚好是从-pi 到 pi
//序号从angle_min开始升序,angle_min 为-pi,因此实际为:
// bin=(atan2f(y,x)-angle_min)/angle_increment
const int bin = (atan2f(y, x) + static_cast<float>(M_PI)) / RESOLUTION;
if ((bin >= 0) && (bin < static_cast<int>(SIZE)))
{
//range[] 的值是平面距离
scan->ranges[bin] = sqrtf(x * x + y * y);
scan->intensities[bin] = i;
}
}
}
}
else
{
ROS_WARN_ONCE("VelodyneLaserScan: PointCloud2 fields in unexpected order. Using slower generic method.");
if (offset_i >= 0)
{
scan->intensities.resize(SIZE);
sensor_msgs::PointCloud2ConstIterator<uint16_t> iter_r(*msg, "ring");
sensor_msgs::PointCloud2ConstIterator<float> iter_x(*msg, "x");
sensor_msgs::PointCloud2ConstIterator<float> iter_y(*msg, "y");
sensor_msgs::PointCloud2ConstIterator<float> iter_i(*msg, "intensity");
for ( ; iter_r != iter_r.end(); ++iter_x, ++iter_y, ++iter_r, ++iter_i)
{
const uint16_t r = *iter_r; // ring
if (r == ring)
{
const float x = *iter_x; // x
const float y = *iter_y; // y
const float i = *iter_i; // intensity
const int bin = (atan2f(y, x) + static_cast<float>(M_PI)) / RESOLUTION;
if ((bin >= 0) && (bin < static_cast<int>(SIZE)))
{
scan->ranges[bin] = sqrtf(x * x + y * y);
scan->intensities[bin] = i;
}
}
}
}
else
{
sensor_msgs::PointCloud2ConstIterator<uint16_t> iter_r(*msg, "ring");
sensor_msgs::PointCloud2ConstIterator<float> iter_x(*msg, "x");
sensor_msgs::PointCloud2ConstIterator<float> iter_y(*msg, "y");
for (; iter_r != iter_r.end(); ++iter_x, ++iter_y, ++iter_r)
{
const uint16_t r = *iter_r; // ring
if (r == ring)
{
const float x = *iter_x; // x
const float y = *iter_y; // y
const int bin = (atan2f(y, x) + static_cast<float>(M_PI)) / RESOLUTION;
if ((bin >= 0) && (bin < static_cast<int>(SIZE)))
{
scan->ranges[bin] = sqrtf(x * x + y * y);
}
}
}
}
}
//发布 消息
pub_.publish(scan);
}
else
{
ROS_ERROR("VelodyneLaserScan: PointCloud2 missing one or more required fields! (x,y,ring)");
}
}
//动态参数回调,设置ring 以及revolution
void VelodyneLaserScan::reconfig(VelodyneLaserScanConfig& config, uint32_t level)
{
cfg_ = config;
}
} // namespace velodyne_laserscan
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