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我今天嘗試的用Mac OS 10.15 安裝 ROS2.0 Eloquent

根據這個網站安裝 https://index.ros.org/…/Ins…/Eloquent/OSX-Development-Setup/

可是在執行. ~/ros2_eloquent/install/setup.bash 設置環境時，卻出現

not found: "/Users/XXX/ros2_eloquent/local_setup.bash"

請問有人有遇過相同問題嗎？

想問個小問題，macbook裝virtualbox開ubuntu功能列消失了怎麼叫也不出現、是哪裡出了什麼問題？

Ros2 安裝在Mac OS Mojave有些問題想請教

我依照https://index.ros.org//doc/ros2/Installation/Crystal/OSX-Install-Binary/

安裝，但執行ros2 run demo_nodes_cpp talker時他會發出警告

dyld: Library not loaded: /usr/local/opt/poco/lib/libPocoFoundation.60.dylib

Referenced from: /Users/chenwei/ros2-osx/lib/librosidl_typesupport_c.dylib

Reason: image not found

然後我到路徑裡面尋找，發現只有libPocoFoundation.62.dylib，沒有libPocoFoundation.60.dylib

所以我猜需要將poco的版本降下來，可是我發現我不會用brew 降版本，有哪位大大知道嗎？

Announcing ROSCon 2019 Diversity Scholarships -
The ROSCon 2019 organizing committee aims for ROSCon to represent the entire ROS community, which is diverse and global. Whoever you are, whatever you do, and wherever you do it, if you’re interested in ROS, then we want you to join us at ROSCon in Macau October 31st – November 1st.
To help reduce financial barriers to conference attendance, the ROSCon organizing committee is offering a number of scholarships to members of traditionally underrepresented groups in the robotics community.
We invite applications from members of groups that have been traditionally underrepresented in the robotics community, including but not limited to: women, people in LGBTQIA communities, people with disabilities, people from racial and/or ethnic minorities in the robotics community, and people from developing nations who may not otherwise be able to attend ROSCon. See official announcement at

宣佈roscón 2019年多樣性獎學金-
Roscón 2019組織委員會旨在讓roscón代表整個ros社羣, 這個社羣是多樣化和全球性的. 無論你是誰, 無論你做甚麼, 無論你做甚麼, 如果你對ros感興趣, 那麼我們希望你在十月31日至十一月1日澳門的roscon加入我們.
為了幫助減少出席會議的財務障礙, roscón組織委員會正在向機器人界代表不足的群體提供了一些獎學金.
我們請機器人社羣中代表不足的團體成員申請, 包括但不限於: 婦女, lgbtqia社羣的人, 殘疾人, 機器人社羣的種族和/或少數民族的人, 以及來自 否則無法參加roscón的發展中國家. 見http://bit.ly/2GxAFIT的官方公告

· 查看原文 · 為此翻譯評分

https://roscon.ros.org/2019/

ROSCon 2019 in Macau.
October 31st - November 1st, 2019
----------------------------------------
Early registration deadline
August 24th, 2019

Late registration starts
October 1st, 2019

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各位好，潛水許久初次發文請多指教
(沒聽過ROS2的可跳轉下面)

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就像許多人可能都已經知道的 ROS 2 - C版 Crystal Clemmys 已經在 12/15 正式釋出，其中包含了許多項眾所矚目的重大功能，例如：
* 更加完整的launch 功能，包含條件式，巢狀啟動，引數導引，以及結點啟動參數等等
* 首次正式釋出 Action 的測試碼
* 記錄回放管理 rosbag2 終於有啦
* 好用的系統監測/解蟲工具ROSQT (rqt)
* 完整的parameter功能函示介面
* ROS 時間函式庫與函式介面 (Python)
* Python 節點參數傳遞
* 原生支援 Ubuntu 18.04 / Mac OS X 10.12 / Windows 10，並且可以在16.04上面成功編譯

另外，在大家常用的官方節點包方面，則是有以下這些在ROS1中常見的套件都可以在C版上使用：
* gazebo_ros_pkgs
* image_transport
* navigation2
* TurtleBot3

當然，現在 ROS2 還在基礎功能植入的階段，很多API可能都還會有變化。不過看起來到了C版，主要的功能都已經到齊了！ (Nodes, Parameter, Service, Action, Launch 等等...) 新版的網頁現在看起來慢慢的架構也要成形了(雖然個人覺得現在還沒有很好用就是了....)
如果你是 ROS 生態圈的新手，建議還是先從目前線上資源比較豐富的 ROS1 下手，Kinetic 跟 Melodic看起來應該會是最主要的兩個版本了。

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https://index.ros.org/doc/ros2/
https://index.ros.org/doc/ros2/Release-Crystal-Clemmys/
https://discourse.ros.org/t/ros-2-crystal-clemmys-rele…/7137
http://www.ros.org/reps/rep-2000.html…
https://github.com/ros2/ros2/issues/529
https://github.com/ros-planning/navigation2

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對於ROS2 比較不熟悉的朋友：ROS2 是 Open Robotics 公司開發 ROS 系統的下一代，旨在改進許多基於ROS1藉由原生ROSTCP/ROSUDP 系統上一開始沒有考量到的設計點。例如可程式化的節點(Node)管理與啟動、節點生命週期的定義、新的C++11和Pyhon3的原生支援。
我個人試過目前覺得最好用的點，在於它使用DDS (資料散步系統)做為節點中通訊的方式，讓新手終於不用再那邊常常 ROS_MASTER_URI / ROS_IP 搞半天。另外，除了可以直接藉由DDS中QoS(網路服務品質)參數設定來針對不同網路結構做最佳化外，DDS的跨平台特性也使 ROS2 首度支援跨平台，其中最令人期待的就是嵌入式系統 (embedded system)，以及即時作業系統(Real Time Operating System) 的原生支援。白話文：以後寫單晶應用就不用再自己寫通訊跟 driver node 啦！！！

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不知道大家對於ROS2有沒有甚麼想像與期待？歡迎各位有消息一起來分享！

將ROS安裝在Mac OS,
安裝時，要用文件程式打開 install
之後將
rosdep install --from-paths . --ignore-src --rosdistro ${ROS_DISTRO} -y --as-root pip:no

改成

rosdep --skip-keys google-mock install --from-paths . --ignore-src --rosdistro ${ROS_DISTRO} -y --as-root pip:no

用來解決
ROS No definition of [google-mock] for OS [osx]的問題

安裝目錄會安裝在
/opt/ros/(dir)裡

https://github.com/mikepurvis/ros-install-OS X

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[LIVE STREAMING] Duckietown AI Driving Olympics
http://www.theconstructsim.com/ros-developers-live-class-d…/

The Duckietown project is devoted to teaching AI and machine learning with robots. Recently they launched the AI-Do Driving Olympics competition about self-driving cars.

In this series of three Live Classes we are going to see how to use simulations to program de Duckiebots solve the AI-Do competition and program simple self-driving cars.

▸ EP1 | Sep 11th, 2018
In this Live Class we'll see:
- How to set up a full Gazebo simulation of a Duckietown and Duckiebots with the proper ROS interface
- How to access the sensors and actuators of the Duckiebots
- How to create a simple navigation program for the robot

▸ EP 2 | Sep 18th, 2018
In this Live Class we'll see:
- How to use OpenAI to create a robot that follows the lines. We will use reinforcement Learning (DeepQ learning)

▸ EP 3 | Sep 25th, 2018
In this Live Class we'll see:
- How to manage traffic, avoiding other Duckiebots and handling intersections. We will use deep learning to train the robots.

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[ROS Developers LIVE-Classes List]

Upcoming ROS LIVE streams:
http://www.theconstructsim.com/ros-developers-live-class-d…/
12 Jun | How to create an OpenAI environment for your robotic problem
19 Jun | Using Tensorflow with ROS

Previous ROS Developers LIVE-Class:
- #20: Simulate an Industrial Environment
http://www.theconstructsim.com/ros-developers-live-class-2…/

- #19: Let’s Use Gazebo Plugins
http://www.theconstructsim.com/ros-developers-live-class-1…/

- #18 : Let’s Simulate a World in Gazebo Simulator http://www.theconstructsim.com/ros-developers-live-class-1…/

- #17: Let's Simulate a Robotic Arm With Gazebo
https://youtu.be/DJwnZSaHy7s

- #16: How to build a Gazebo robot simulation
https://youtu.be/q01dDxeHTMs

- #15: Using ROS TF to transform sensor data
https://youtu.be/dBATvRhvGRI

- #14: How To Control Robot Joints With ROS
https://youtu.be/M4KF2c3OMSI

- #13: ROS Navigation Stack How To
https://youtu.be/fTizQneURWo

- #12: How to use ROS with industrial robots (ROS Industrial)
https://youtu.be/BCDFvMw6N-8

- #11: Visually Programming ROS State Machines (Round #3)
https://youtu.be/ZLv5iCSnR5c

- #10: Visually Programming ROS State Machines (Round #2)
https://youtu.be/lKkP5qhFbHQ

- #9: Visually Programming ROS State Machines (Round #1)
https://youtu.be/jrV5jRs1SJc

- #8: How to recognize faces with the ROS face recognition package
https://youtu.be/yENvskEKhJk

- #7: OpenAI+ROS Robot: Practical section
https://youtu.be/FYdS3-c2lKw

- #6: How to use OpenAI to train your robot
https://youtu.be/L7mlz7I8RbI

- #5: Simulating a Drone from Scratch
https://youtu.be/l6hVfVK_YWw

- #4: Carrot Navigation using AR Tags
https://youtu.be/QkUZWRe5f4I

- #3: rotating laser mounted on a vehicle
https://youtu.be/W2VNNMiiN-Q

- #2: Merging Odometry and IMU data for robot localization
https://youtu.be/nQZeAafDEJE

- #1: Building 3D pointclouds from rotating lasers
https://youtu.be/5CvqJ5EFbE4

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[Resources about Using OpenAI with ROS]
-> Article | Using OpenAI with ROS
http://www.theconstructsim.com/using-openai-ros/
OpenAI has released the Gym, a toolkit for developing and comparing reinforcement learning (RL) algorithms. That toolkit is a huge opportunity for speeding up the progress in the creation of better reinforcement algorithms, since it provides an easy way of comparing them, on the same conditions, independently of where the algorithm is executed.

The toolkit is mainly aimed at the creation of RL algorithms for a general abstract agent. Here, we are interested in applying it to the control of robots (of course!). Specifically, we are interested in ROS based robots. That is why, in this post we describe how to apply the OpenAI Gym to the control of a drone that runs with ROS.

-> Machine Learning with OpenAI Gym on ROS Development Studio
http://www.theconstructsim.com/machine-learning-openai-gym…/
You can now train your robot to navigate through an environment filled with obstacles just based on the sensor inputs, with the help of OpenAI Gym. In April 2016, OpenAI introduced “Gym”, a platform for developing and comparing reinforcement learning algorithms. Reinforcement learning is an area of machine learning that allows an intelligent agent (for example, robot) to learn the best behaviors in an environment by trial-and-error. The agent takes actions in an environment so as to maximize its rewards. We have deployed the gym_gazebo package from Erle Robotics S.L. in the ROS Development Studio. It enables the users to test their reinforcement learning for their robots in Gazebo.

-> Video Tutorials
* [ROS tutorial] OpenAI Gym For ROS based Robots 101 Course: https://youtu.be/o9FpZ1QQqcc
* How to start with OpenAI + ROS fast: http://www.theconstructsim.com/start-openai-ros-fast/
* LIVE-Class: How to use OpenAI to train your robot (Part1): https://youtu.be/L7mlz7I8RbI
* LIVE-Class: How to use OpenAI to train your robot (Part2): https://youtu.be/FYdS3-c2lKw

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