接着上述的工作，在將近一個月的摸索實踐中，終於完成了抓取的工作。其中包含tf座標系的轉換以及最後位置的調試工作。
這一篇先講述如果進行根據camera_link以及base_link之間的轉換關係完成一個點、一組點的進階座標轉換。接着之前的手眼標定，連接起相機以及機械手臂的tf_tree.
#rosrun rqt_tf_tree rqt_tf_tree
這裏要注意在camera_link中包含的子樹camera_rgb_optical_frame以及camera_rgb_frame兩個座標系是不同的，從rviz裏面來看其position大致重合，但是orentation是不一樣的，而且相機檢測到的可樂罐的位置座標所屬是在camera_rgb_optical_frame下的，所以在轉換過程中（TF點的transform）一定要注意函數裏面的參數是什麼意思，座標系代表的是哪一個座標系，不然不清不楚在後面的位置標定過程中會出現很多錯誤。
開始tf轉換過程的總結。首先當然是參考的我們官網教程，不可否認，雖然在他人的csdn博客可以學到或者拿到想看的內容，但是相比之下還是官網內容比較詳細，如果某句程序、函數不懂可以很快的理解並修改。下面是核心的subscriber以及publisher（c++版本以及python版本）
http://wiki.ros.org/ROS/Tutorials/WritingPublisherSubscriber%28c%2B%2B%29
http://wiki.ros.org/ROS/Tutorials/WritingPublisherSubscriber%28python%29
以及依然可以替代參考的幾篇csdn博客
https://blog.csdn.net/Will_Ye/article/details/79485964
https://blog.csdn.net/start_from_scratch/article/details/50762293/
https://blog.csdn.net/Will_Ye/article/details/79996311
由開發流程來看，首先要查看所要得到的物體位置信息（如何挖數據），接着要轉換一個點從camera_link到base_link下，接着便是將物體的實時位置從camera_rgb_optical_frame到base_link座標系下面。
這裏插一個在pyhon裏面查看所用到的函數：
ipython()
help(tf.TransformBroadcaster.sendTransform)
可以查看該函數的參數及相關信息。
-----------------------------------------------------1---------------------------------------------------------
1.查看物體位置信息：
之前已經提到RecognizedObjectArray這個數組存放的是物體的位置信息，包括position orentation 以及header等等。這個數組是linemod算法在識別到物體位置以後將位置存儲到這裏（並且以話題的形式publish消息，所以我們能在rviz裏面看到物體的標定位置）
下面是之前定義存放識別到物體信息存放的數組位置listener.py（寫的一個簡單的判斷打印物體信息的位置）
#!/usr/bin/env python
#coding=utf-8
import rospy
# from std_msgs.msg import String
from object_recognition_msgs.msg import RecognizedObjectArray
def callback(data):
if len(data.objects)>0:
print "coke detected~~~~~~~~~~~~~~~~~~~~"
rospy.loginfo(rospy.get_caller_id() + 'heard %s', data.objects[0].pose.pose.pose)
# rospy.loginfo(rospy.get_caller_id() + 'heard %s', data.objects[0].pose)
else:
print "nothing detected................."
def listener():
# In ROS, nodes are uniquely named. If two nodes with the same
# name are launched, the previous one is kicked off. The
# anonymous=True flag means that rospy will choose a unique
# name for our 'listener' node so that multiple listeners can
# run simultaneously.
rospy.init_node('listener', anonymous=True)
rospy.Subscriber('recognized_object_array', RecognizedObjectArray, callback)
# spin() simply keeps python from exiting until this node is stopped
rospy.spin()
if __name__ == '__main__':
listener()
---------------------------------------關於import-----------------------------------------
from A模塊 import B函數=import A 使用A.B（參數）。要注意的是雖然使用from import以後不需要在函數名加前綴，但是B函數只默認是A模塊的函數（如果同名的話），這樣同名但是分屬不同模塊 不同功能的函數就會造成衝突。所以優先使用import ,之後使用 A模塊.B函數（C參數）的形式。
------------------------------------------------------------------------------------------------
這個程序只是打印物體的位置信息並且加了一個簡單的判斷，讓我們來看爲什麼要這樣寫（怎麼來挖數據）。挖數據核心主要是rospy.Subscriber('recognized_object_array', RecognizedObjectArray, callback)用來訂閱RecognizedObjectArray話題並且一旦接收到消息就調用回調函數callback。而另一句打印 rospy.loginfo(rospy.get_caller_id() + 'heard %s', data.objects[0].pose.pose.pose) ，前面的id沒什麼用，後面的回調函數先判斷是不是空的內容（是否識別到物體），data指代了RecognizedObjectArray的所有信息，也就是一個形參。用下面的命令來查看數據：
#rosmsg show RecognizedObjectArray
用來查看發佈的消息的類型以及包含的內容
這樣來看data=RecognizedObjectArray,然後data.object[]=RecognizedObjectArray[],也就是指向消息的第二個變量object[]數組，如果用object[0]代表取當前檢測到的第一個物體位置信息的數組信息。繼續挖，data.object[]=RecognizedObjectArray[]包含了幾個對象，比如header、type、confidence、pose(未截到圖)等等以及他們對應的數據類型。運行listener來繼續看
#rosrun ur10_rg2_moveit_config listener.py打印識別到的物體位置
上面是隻挖到data.object[].pose。這樣來看可以看到，data.object[].pose.pose.pose即指到只有posetion和orientation數據處。這樣我們就可以挖到指定的數據，並且對挖數據有一個直觀的學習瞭解。
-----------------------------------------------------2---------------------------------------------------------
2.將一個點從camera_link到base_link:
首先說明之前標定兩座標系以後以及發佈了一個關係：在創建的tf_broadcaster廣播兩座標關係並且放置在tf::transform
函數中。
#rosrun robot_setup_tf tf_broadcaster
#include <ros/ros.h>
#include <tf/transform_broadcaster.h>
int main(int argc, char** argv){
ros::init(argc, argv, "robot_tf_publisher");
ros::NodeHandle n;
ros::Rate r(100);
tf::TransformBroadcaster broadcaster;
while(n.ok()){
broadcaster.sendTransform(
tf::StampedTransform(
tf::Transform(tf::Quaternion(0.0144077350003, -0.0295559697343, -0.0183787903043, 0.999290289101), tf::Vector3(0.244332058703, -0.0155924006203, -0.0434545849503)),
ros::Time::now(),"base_link", "camera_link"));
r.sleep();
}
}
編寫了一個tf_listener_OnePosetransform.cpp 用於單獨發佈一個點，這個以後在位置標定也有作用：
#rosrun robot_setup_tf tf_listener_OnePosetransform
#include <ros/ros.h>
// #include <geometry_msgs/PointStamped.h>
#include "geometry_msgs/PoseStamped.h"
#include "geometry_msgs/Pose.h"
#include <tf/transform_listener.h>
#include <tf/transform_broadcaster.h>
#include <visualization_msgs/MarkerArray.h>
geometry_msgs::PoseStamped real_pose;
geometry_msgs::PoseStamped transed_pose;
void transformPose(const tf::TransformListener& listener){
//we'll create a point in the base_laser frame that we'd like to transform to the base_link frame
// geometry_msgs::PointStamped laser_point;
// geometry_msgs::PoseStamped msg;
// laser_point.header.frame_id = "camera_link";
// real_pose.header.frame_id = "camera_link";
real_pose.header.frame_id = "camera_rgb_optical_frame";
// real_pose.header.frame_id = "camera_rgb_frame";
//we'll just use the most recent transform available for our simple example
// laser_point.header.stamp = ros::Time();
real_pose.header.stamp = ros::Time();
real_pose.pose.position.x = -0.0521919690073;
real_pose.pose.position.y = 0.0947469994426;
real_pose.pose.position.z = 0.928996682167;
real_pose.pose.orientation.w = 0.487851679325;
real_pose.pose.orientation.x = 0.518789410591;
real_pose.pose.orientation.y = -0.516209602356;
real_pose.pose.orientation.z = 0.47580036521;
//just an arbitrary point in space
try{
// geometry_msgs::PointStamped base_point;
// listener.transformPoint("base_link", laser_point, base_point);
listener.transformPose("base_link", real_pose, transed_pose);
ROS_INFO("camera_rgb_frame: (%.2f, %.2f. %.2f, %.2f, %.2f, %.2f, %.2f) -----> base_link: (%.4f, %.4f, %.4f, %.4f, %.4f, %.4f, %.4f) at time %.2f",
real_pose.pose.position.x, real_pose.pose.position.y, real_pose.pose.position.z, real_pose.pose.orientation.x, real_pose.pose.orientation.y, real_pose.pose.orientation.z, real_pose.pose.orientation.w,
transed_pose.pose.position.x, transed_pose.pose.position.y, transed_pose.pose.position.z, transed_pose.pose.orientation.x, transed_pose.pose.orientation.y, transed_pose.pose.orientation.z, transed_pose.pose.orientation.w, transed_pose.header.stamp.toSec());
}
catch(tf::TransformException& ex){
ROS_ERROR("Received an exception trying to transform a point from \"camera_rgb_optical_frame\" to \"base_link\": %s", ex.what());
}
}
int main(int argc, char** argv){
ros::init(argc, argv, "tf_listener_Posetransform");
ros::NodeHandle n;
tf::TransformListener listener(ros::Duration(10));
//we'll transform a point once every second
ros::Timer timer = n.createTimer(ros::Duration(1.0), boost::bind(&transformPose, boost::ref(listener)));
ros::Publisher my_publisher_realPose = n.advertise<geometry_msgs::PoseStamped>("real_pose", 1000);
ros::Publisher my_publisher_transedPose = n.advertise<geometry_msgs::PoseStamped>("transed_pose", 1000);
ros::Rate loop_rate(10);
while (ros::ok())
{
my_publisher_transedPose.publish(transed_pose);
my_publisher_realPose.publish(real_pose);
ros::spinOnce();
loop_rate.sleep();
}
ros::spin();
return 0;
}
這裏的點是之後自己檢測到物體的點自己寫進去的，實際中可以修改來幫助自己查看點的位置變化。這裏的real_pose以及transed_pose都是geometry_msgs::PoseStamped消息類型的，以後查看轉換信息也要在這裏查看。tf_listener_OnePosetransform文件中只定義了一個節點，但是它同時完成了訂閱（subscriber）以及發佈（publish）的工作。listener.transformPose("base_link", real_pose, transed_pose);監聽之前發佈的兩座標系關係，利用之前的transformPose函數即可將camera_link下的一個座標位置（自定義的real_pose座標）轉換到base_link下面。另外一定要注意座標所屬的座標系real_pose.header.frame_id = "camera_rgb_optical_frame"。%.2f表示f爲浮點型數據，2表示只展示到小數點後兩位，所以可以改爲4位。1000代表緩存消息的最大內存。
----------------------------------關於錯誤 輸出位置結果 nan nan nan nan--------------------------------
如果在輸出過程中，位置結果出現nan nan nan nan ,表示位置信息錯誤，可能的原因是節點發送的消息 信息並不符合規範，nan表示not a number。所以應該檢查檢點發送的信息 用rosmsg echo /path topic 來檢查。
----------------------------------------------------------------------------------------------------------------------------
接着就是要將這兩個點發布出去
ros::Publisher my_publisher_realPose = n.advertise<geometry_msgs::PoseStamped>("real_pose", 1000);
my_publisher_realPose是自己命名的消息名，消息類型爲geometry_msgs::PoseStamped，話題名爲real_pose(這樣就可以在rviz裏面add poseStamped類型，選擇相應話題即可在rviz裏面顯示觀察。）。
上面那一行程序只是說要發佈這個消息，但是具體的發佈操作卻是下一步：
my_publisher_realPose.publish(real_pose);
這樣我們就完成了一個自定義點的從camera_rgb_optical_frame到base_link的轉換。
用rosmsg即可查看： 要挖的話也是一樣的道理。
rosmsg show geometry_msgs/PoseStamped 打印poseStamped的消息
-----------------------------------------------------3---------------------------------------------------------
3.將物體位置從camera_rgb_optical_frame到base_link轉換
#rosrun robot_setup_tf tf_listener
創建tf_listener.cpp（包括所需的依賴項 創建過程在官網的編寫subscriber以及publisher都有提到，讀者可以自行到文章最前面查看）
(原諒我 在tf這塊參考代碼比較多的是cpp文件，所以在修改完程序以後每次都得cmake重新編譯，而且訂閱和發佈都是cpp來完成的，不過在最後的控制機械臂運行的python程序中又變成在python裏面訂閱這個消息，所以讀者要注意博主在這塊的限制（更熟悉cpp一點）)。
#include <ros/ros.h>
#include "geometry_msgs/PoseStamped.h"
#include "geometry_msgs/Pose.h"
#include <tf/transform_listener.h>
#include <tf/transform_broadcaster.h>
// #include "std_msgs/String.h"
#include <object_recognition_msgs/RecognizedObjectArray.h> //using ORK
#include <visualization_msgs/MarkerArray.h>
//實時轉換採集到的可樂罐的位置點轉換
std::string Object_id = "";
double Object_assurance = 0;
geometry_msgs::PoseStamped Object_pose;
geometry_msgs::PoseStamped transed_pose;
bool firstCB = false;
void myCallback(const object_recognition_msgs::RecognizedObjectArray objects_msg) //回調函數
{
double confident = 0;
int id = -1;
if (firstCB == false && (int)objects_msg.objects.size() == 1) {
Object_id.assign(objects_msg.objects[0].type.key.c_str());
firstCB = true;
}
for (int i = 0; i < objects_msg.objects.size(); ++i) {
if (Object_id.compare(objects_msg.objects[i].type.key.c_str()) == 0) {
if (objects_msg.objects[i].confidence > confident) {
confident = objects_msg.objects[i].confidence;
id = i;
}
}
}
if (id >= 0) {
Object_pose.pose = objects_msg.objects[id].pose.pose.pose;
Object_assurance = objects_msg.objects[id].confidence;
} else {
confident = 0;
}
}
void transformPose(const tf::TransformListener& listener){
//we'll create a point in the base_laser frame that we'd like to transform to the base_link frame
// geometry_msgs::PointStamped laser_point;
// geometry_msgs::PoseStamped transed_pose;
// laser_point.header.frame_id = "camera_link";
// msg.header.frame_id = "camera_link";
// Object_pose.header.frame_id = "camera_rgb_frame";
Object_pose.header.frame_id = "camera_rgb_optical_frame";
//we'll just use the most recent transform available for our simple example
// laser_point.header.stamp = ros::Time();
ROS_INFO("Waiting for the object");
if (Object_assurance > 0.8) {
ROS_INFO("Best Similarity = %f ", Object_assurance);
ROS_INFO("pose x is: %f", Object_pose.pose.position.x);
ROS_INFO("pose y is: %f", Object_pose.pose.position.y);
ROS_INFO("pose z is: %f", Object_pose.pose.position.z);
bool tferr = true;
while (tferr) {
tferr = false;
try{
listener.transformPose("base_link", Object_pose, transed_pose);
}
catch (tf::TransformException &exception) {
ROS_ERROR("Received an exception trying to transform a point from \"camera_rgb_frame\" to \"base_link\": %s", exception.what());
tferr = true;
ros::Duration(0.1).sleep();
ros::spinOnce();
}
} //while
ROS_INFO("camera_rgb_optical_frame: (%.2f, %.2f. %.2f, %.2f, %.2f, %.2f, %.2f) -----> base_link: (%.2f, %.2f, %.2f, %.2f, %.2f, %.2f, %.2f) at time %.2f",
Object_pose.pose.position.x, Object_pose.pose.position.y, Object_pose.pose.position.z, Object_pose.pose.orientation.x, Object_pose.pose.orientation.y, Object_pose.pose.orientation.z, Object_pose.pose.orientation.w,
transed_pose.pose.position.x, transed_pose.pose.position.y, transed_pose.pose.position.z, transed_pose.pose.orientation.x, transed_pose.pose.orientation.y, transed_pose.pose.orientation.z, transed_pose.pose.orientation.w, transed_pose.header.stamp.toSec());
} //if
} //void
int main(int argc, char** argv){
ros::init(argc, argv, "robot_tf_listener");
ros::NodeHandle n;
ros::Subscriber my_subscriber_object= n.subscribe("recognized_object_array",1000,myCallback);
tf::TransformListener listener(ros::Duration(10));
//we'll transform a point once every second
ros::Timer timer = n.createTimer(ros::Duration(1.0), boost::bind(&transformPose, boost::ref(listener)));
ros::Publisher my_publisher_transPose = n.advertise<geometry_msgs::PoseStamped>("transformPose", 1000);
ros::Publisher my_publisher_ObjectPose = n.advertise<geometry_msgs::PoseStamped>("ObjectPose", 1000);
ros::Rate loop_rate(10);
while (ros::ok())
{
// std_msgs::String msg;
// msg.data = ss.str();
// ROS_INFO("=====transformedPose======: (%.2f, %.2f, %.2f, %.2f, %.2f, %.2f, %.2f)", transed_pose.pose.position.x, transed_pose.pose.position.y, transed_pose.pose.position.z, transed_pose.pose.orientation.x, transed_pose.pose.orientation.y, transed_pose.pose.orientation.z, transed_pose.pose.orientation.w);
my_publisher_transPose.publish(transed_pose);
my_publisher_ObjectPose.publish(Object_pose);
ros::spinOnce();
loop_rate.sleep();
}
ros::spin();
return 0;
}
這個就是最終的tf變換過程所需要的內容程序。這個程序中完成了三件事：
（1）物體信息的訂閱、簡單判斷以及發佈
（2）將物體位置從camera_rgb_optical_frame到base_link轉換
(3) 將轉換後的位置信息發佈出去。
這段程序和之前一個點的轉換過程類似所以不再贅述，值得注意的是：
geometry_msgs::PoseStamped Object_pose;
geometry_msgs::PoseStamped transed_pose;
物體的位置以及轉換後的位置要聲明爲全局變量。
其他：
終於在十月份的尾巴完成了這個小項目的工作任務，當然今天只是對tf這一塊兒做個簡單總結，明天繼續總結完剩下的調整標定工作，記錄怎樣分析錯誤並一步步解決最終使機械臂抓取到物體。像下面就是之前一直卡的一個情況，下一篇博客也是最爲重要也是最完整的找自己出現的錯誤，修改程序並抓到物體，也可以發自己的測試視頻。目前來看這個算法在抓取任務方面還是蠻靠譜的，雖然穩定性還是不是很好，尤其在邊遠的位置處檢測效果不好（很容易卡主沒有檢測結果），當然只要有結果就能抓起來證明自己在其他的程序並沒有問題，算法的問題也是今後論文創新的關鍵。
記錄自己的一月，完成明天的最後內容的總結就可以繼續下一步的工作了，繼續努力，↖(^ω^)↗加油！
附：還有一個可以直接運行得到當前機械手位置的python程序 算作一個插件
#rosrun ur10_rg2_moveit_config my_pose_print.py打印當前機械手位置
#!/usr/bin/env python
# Software License Agreement (BSD License)
#
# Copyright (c) 2013, SRI International
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of SRI International nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# Author: Acorn Pooley, Mike Lautman
## BEGIN_SUB_TUTORIAL imports
##
## To use the Python MoveIt! interfaces, we will import the `moveit_commander`_ namespace.
## This namespace provides us with a `MoveGroupCommander`_ class, a `PlanningSceneInterface`_ class,
## and a `RobotCommander`_ class. (More on these below)
##
## We also import `rospy`_ and some messages that we will use:
##
import math
import tf
import sys
import copy
import rospy
import moveit_commander
import moveit_msgs.msg
import geometry_msgs.msg
from math import pi
from std_msgs.msg import String
from moveit_commander.conversions import pose_to_list
from ur_control.srv import *
import random
class MoveGroupPythonIntefaceTutorial(object):
"""MoveGroupPythonIntefaceTutorial"""
def __init__(self):
super(MoveGroupPythonIntefaceTutorial, self).__init__()
## BEGIN_SUB_TUTORIAL setup
##
## First initialize `moveit_commander`_ and a `rospy`_ node:
moveit_commander.roscpp_initialize(sys.argv)
rospy.init_node('end_effector_pose_print',
anonymous=True)
## Instantiate a `RobotCommander`_ object. This object is the outer-level interface to
## the robot:
robot = moveit_commander.RobotCommander()
## Instantiate a `PlanningSceneInterface`_ object. This object is an interface
## to the world surrounding the robot:
scene = moveit_commander.PlanningSceneInterface()
## Instantiate a `MoveGroupCommander`_ object. This object is an interface
## to one group of joints. In this case the group is the joints in the Panda
## arm so we set ``group_name = panda_arm``. If you are using a different robot,
## you should change this value to the name of your robot arm planning group.
## This interface can be used to plan and execute motions on the Panda:
group_name = "manipulator"
group = moveit_commander.MoveGroupCommander(group_name)
## We create a `DisplayTrajectory`_ publisher which is used later to publish
## trajectories for RViz to visualize:
display_trajectory_publisher = rospy.Publisher('/move_group/display_planned_path',
moveit_msgs.msg.DisplayTrajectory,
queue_size=20)
## END_SUB_TUTORIAL
## BEGIN_SUB_TUTORIAL basic_info
##
## Getting Basic Information
## ^^^^^^^^^^^^^^^^^^^^^^^^^
# We can get the name of the reference frame for this robot:
planning_frame = group.get_planning_frame()
print "============ Reference frame: %s" % planning_frame
# We can also print the name of the end-effector link for this group:
eef_link = group.get_end_effector_link()
print "============ End effector: %s" % eef_link
# We can get a list of all the groups in the robot:
group_names = robot.get_group_names()
print "============ Robot Groups:", robot.get_group_names()
# Sometimes for debugging it is useful to print the entire state of the
# robot:
print "============ Printing robot state"
print robot.get_current_state()
print ""
## END_SUB_TUTORIAL
# Misc variables
self.box_name = ''
self.robot = robot
self.scene = scene
self.group = group
self.display_trajectory_publisher = display_trajectory_publisher
self.planning_frame = planning_frame
self.eef_link = eef_link
self.group_names = group_names
def print_current_endeffector_pose(self):
print self.group.get_current_pose()
pass
def main():
try:
print "============ Press `Enter` to begin to pose endeffector_pose"
# raw_input()
tutorial = MoveGroupPythonIntefaceTutorial()
rospy.sleep(1.0)
while not rospy.is_shutdown():
print("---")
tutorial.print_current_endeffector_pose()
rospy.sleep(0.5)
pass
print "endeffector_pose complete!"
except rospy.ROSInterruptException:
return
except KeyboardInterrupt:
return
if __name__ == '__main__':
main()
--------------------------------------------------更新2019.7.19--------------------------------------------------------------
因爲最近半年都在準備發論文以及準備雅思，所以都沒有登csdn回覆。希望8.24雅思順利，繼續努力把。之後準備好雅思及申請好後，會總結一下今年前兩個半月paper做的3D 物體識別、6D位姿估計以及重疊物體的檢測等內容。
另外，有很多人通過郵箱聯繫到了我我也給出了我的解答。如有問題請發郵件到： [email protected] 最近依然不會回覆csdn。
如果有人感興趣想加入的話，自動化所招實習生啦！！！
【自動化所類腦中心-類腦機器人實習生招聘】
類腦認知機器人算法及應用實習生：主要負責基於ROS的認知機器人開發，要求自動控制及相關專業（或個人十分感興趣），具有機器人ROS開發經驗/python編程基礎者優先，最好能實習6個月以上。我們將提供Baxter機器人、Robotnik機器底盤、NAO機器人等作爲硬件支撐實習生的研究。
有意者請聯繫[email protected]
--------------------------------------------------------7.19--------------------------------------------------------------------------------------
-------------------------------------------------------------------------------2020.3.2更新-------------------------------------------------------------
最近在準備面試，有問題可以聯繫上面的郵箱。最終的文章代碼鏈接以及原文、實現步驟已經在系列終結篇給出。
另外本人畫的場景設計畫在站酷上，歡迎交流www.zcool.com.cn/u/20178144