从零开始用Python、ROS和OpenCV设计并模拟自主移动机器人

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《学习机器人技术:使用Python设计、模拟编程及原型构建交互式自主移动机器人》是一本由Lentin Joseph编著的综合文档,专为那些希望从零开始学习和实践机器人技术的人提供指导。本书以Python编程语言为核心,结合ROS(Robot Operating System,机器人操作系统)和OpenCV(Open Source Computer Vision Library,开源计算机视觉库)来帮助读者实现自主移动机器人的设计与开发。 作者深入浅出地介绍了如何通过Python进行机器人系统的设计,从概念理解到实际操作,包括模拟器的建立,程序的编写,以及机器人原型的制作。首先,读者将掌握如何利用Python的简洁语法来编写控制逻辑和算法,这是机器人智能化的基础。接着,ROS作为一个强大的框架,将展示在分布式系统中的应用,使得机器人能够与其他设备和传感器进行有效通信和协作。 OpenCV在这个过程中扮演着关键角色,它为机器人提供视觉感知的能力,帮助机器理解和处理环境信息,如物体识别、避障和导航。通过集成这两个工具,作者将引导读者如何构建一个具备互动性、自主性的移动机器人,使其能够在特定环境中执行任务。 版权方面,这本书受到2015年Packt Publishing的保护,所有复制、存储或传输必须在事先获得出版商的书面许可,除非是在批评文章或评论中引用部分短小内容。 尽管作者和出版商已尽力确保信息的准确性,但书中提供的所有内容均以现状销售,不承担因使用本书导致的任何直接或间接损失的责任。此外,本书提及的所有公司和产品商标信息,Packt Publishing都尽可能进行了规范标注。 《Learning Robotics Using Python》是一本实用的指南,不仅适合初学者了解机器人开发的基本原理,也对有一定经验的工程师提供了进阶技术和实践经验,是学习和提升机器人技术能力的宝贵资源。
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Effective Robotics Programming with ROS, Third Edition gives you a comprehensive review of ROS, the Robot Operating System framework, which is used nowadays by hundreds of research groups and companies in the robotics industry. More importantly, ROS is also the painless entry point to robotics for nonprofessionals and students. This book will guide you through the installation process of ROS, and soon enough, you will be playing with the basic tools and understanding the different elements of the framework. The content of the book can be followed without any special devices, and each chapter comes with a series of source code examples and tutorials that you can run on your own computer. This is the only thing you need to follow the book. However, we also show you how to work with hardware so that you can connect your algorithms with the real world. Special care has been taken in choosing devices that are affordable for amateur users, but at the same time, the most typical sensors or actuators in robotics research are covered. Finally, the potential of ROS is illustrated with the ability to work with whole robots in a real or simulated environment. You will learn how to create your own robot and integrate it with a simulation by using the Gazebo simulator. From here, you will have the chance to explore the different aspects of creating a robot, such as perceiving the world using computer vision or point cloud analysis, navigating through the environment using the powerful navigation stack, and even being able to control robotic arms to interact with your surroundings using the MoveIt! package. By the end of the book, it is our hope that you will have a thorough understanding of the endless possibilities that ROS gives you when developing robotic systems.What this book covers Chapter 1, Getting Started with ROS, shows the easiest way you must follow in order to have a working installation of ROS. You will see how to install ROS on different platforms, and you will use ROS Kinetic throughout the rest of the book. This chapter describes how to make an installation from Debian packages, compile the sources, and make installations in virtual machines, Docker, and ARM CPU. Chapter 2, ROS Architecture and Concepts, is concerned with the concepts and tools provided by the ROS framework. We will introduce you to nodes, topics, and services, and you will also learn how to use them. Through a series of examples, we will illustrate how to debug a node and visualize the messages published through a topic. Chapter 3, Visualization and Debugging Tools, goes a step further in order to show you powerful tools to debug your nodes and visualize the information that goes through the node's graph along with the topics. ROS provides a logging API that allows you to diagnose node problems easily. In fact, we will see some powerful graphical tools, such as rqt_console and rqt_graph, as well as visualization interfaces, such as rqt_plot and rviz. Finally, this chapter explains how to record and play back messages using rosbag and rqt_bag. Chapter 4, 3D Modeling and Simulation, constitutes one of the first steps in order to implement your own robot in ROS. It shows you how to model a robot from scratch and run it in simulation using the Gazebo simulator. You will simulate sensors, such as cameras and laser range sensors. This will later allow you to use the whole navigation stack provided by ROS and other tools. Chapter 5, The Navigation Stack – Robot Setups, is the first of two chapters concerned with the ROS navigation stack. This chapter describes how to configure your robot so that it can be used with the navigation stack. In the same way, the stack is explained, along with several examples. Chapter 6, The Navigation Stack – Beyond Setups, continues the discussion of the previous chapter by showing how we can effectively make our robot navigate autonomously. It will use the navigation stack intensively for that. This chapter shows the great potential of ROS using the Gazebo simulator and RViz to create a virtual environment in which we can build a map, localize our robot, and do path planning with obstacle avoidance. Chapter 7, Manipulation with MoveIt!, is a set of tools for mobile manipulation in ROS. This chapter contains the documentation that you need to install this package. The chapter also contains example demonstrations with robotic arms that use MoveIt! for manipulation tasks, such as grasping, picking and placing, or simple motion planning with inverse kinematics. Chapter 8, Using Sensors and Actuators with ROS, literally connects ROS with the real world. This chapter goes through a number of common sensors and actuators that are supported inROS, such as range lasers, servo motors, cameras, RGB-D sensors, and GPS. Moreover, we explain how to use embedded systems with microcontrollers, similar to the widely known Arduino boards. Chapter 9, Computer Vision, shows the support for cameras and computer vision tasks in ROS. This chapter starts with drivers available for FireWire and USB cameras so that you can connect them to your computer and capture images. You will then be able to calibrate your camera using the ROS calibration tools. Later, you will be able to use the image pipeline, which is explained in detail. Then, you will see how to use several APIs for vision and integrate OpenCV. Finally, the installation and usage of a visual odometry software is described. Chapter 10, Point Clouds, shows how to use Point Cloud Library in your ROS nodes. This chapter starts with the basics utilities, such as read or write a PCL snippet and the conversions needed to publish or subscribe to these messages. Then, you will create a pipeline with different nodes to process 3D data, and you will downsample, filter, and search for features using