A Systematic Approach to Learning Robot Programming with ROS
暫譯: 系統化學習機器人程式設計與ROS的方法

Wyatt Newman

A Systematic Approach to Learning Robot Programming with ROS

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商品描述

A Systematic Approach to Learning Robot Programming with ROS provides a comprehensive, introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation. The book explores the organization of ROS, how to understand ROS packages, how to use ROS tools, how to incorporate existing ROS packages into new applications, and how to develop new packages for robotics and automation. It also facilitates continuing education by preparing the reader to better understand the existing on-line documentation.

 

The book is organized into six parts. It begins with an introduction to ROS foundations, including writing ROS nodes and ROS tools. Messages, Classes, and Servers are also covered. The second part of the book features simulation and visualization with ROS, including coordinate transforms.

 

The next part of the book discusses perceptual processing in ROS. It includes coverage of using cameras in ROS, depth imaging and point clouds, and point cloud processing. Mobile robot control and navigation in ROS is featured in the fourth part of the book

 

The fifth section of the book contains coverage of robot arms in ROS. This section explores robot arm kinematics, arm motion planning, arm control with the Baxter Simulator, and an object-grabber package. The last part of the book focuses on system integration and higher-level control, including perception-based and mobile manipulation.

 

This accessible text includes examples throughout and C++ code examples are also provided at https://github.com/wsnewman/learning_ros

商品描述(中文翻譯)

《以系統化方式學習機器人程式設計與 ROS》提供了對 ROS 重要組件的全面介紹，透過詳細的簡單程式碼範例及其相應的操作理論進行說明。本書探討了 ROS 的組織結構、如何理解 ROS 套件、如何使用 ROS 工具、如何將現有的 ROS 套件整合到新應用中，以及如何為機器人和自動化開發新套件。它還通過幫助讀者更好地理解現有的線上文檔，促進持續教育。

本書分為六個部分。首先介紹 ROS 的基礎，包括撰寫 ROS 節點和 ROS 工具。還涵蓋了訊息、類別和伺服器。第二部分專注於使用 ROS 進行模擬和視覺化，包括座標轉換。

接下來的部分討論了 ROS 中的感知處理。內容包括在 ROS 中使用相機、深度影像和點雲，以及點雲處理。第四部分則介紹了 ROS 中的移動機器人控制和導航。

第五部分涵蓋了 ROS 中的機器手臂。這一部分探討了機器手臂的運動學、手臂運動規劃、使用 Baxter 模擬器進行手臂控制，以及一個物體抓取套件。最後一部分專注於系統整合和高階控制，包括基於感知的移動操作。

這本易於理解的書籍中包含了多個範例，並且提供了 C++ 程式碼範例，網址為 https://github.com/wsnewman/learning_ros。

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