Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms
暫譯: 自動化機器人入門：機構、感測器、致動器與演算法

Correll, Nikolaus, Hayes, Bradley, Heckman, Christoffer

Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms

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商品描述

A comprehensive introduction to the field of autonomous robotics aimed at upper-level undergraduates and offering additional online resources.

Textbooks that provide a broad algorithmic perspective on the mechanics and dynamics of robots almost unfailingly serve students at the graduate level. Introduction to Autonomous Robots offers a much-needed resource for teaching third- and fourth-year undergraduates the computational fundamentals behind the design and control of autonomous robots. The authors use a class-tested and accessible approach to present progressive, step-by-step development concepts, alongside a wide range of real-world examples and fundamental concepts in mechanisms, sensing and actuation, computation, and uncertainty. Throughout, the authors balance the impact of hardware (mechanism, sensor, actuator) and software (algorithms) in teaching robot autonomy.

Features:

  • Rigorous and tested in the classroom
  • Written for engineering and computer science undergraduates with a sophomore-level understanding of linear algebra, probability theory, trigonometry, and statistics
  • QR codes in the text guide readers to online lecture videos and animations
  • Topics include: basic concepts in robotic mechanisms like locomotion and grasping, plus the resulting forces; operation principles of sensors and actuators; basic algorithms for vision and feature detection; an introduction to artificial neural networks, including convolutional and recurrent variants
  • Extensive appendices focus on project-based curricula, pertinent areas of mathematics, backpropagation, writing a research paper, and other topics
  • A growing library of exercises in an open-source, platform-independent simulation (Webots)

    • 商品描述(中文翻譯)

    針對高年級本科生的自動化機器人領域的全面介紹，並提供額外的線上資源。

    提供廣泛算法視角的教科書幾乎總是針對研究生層級的學生。自動化機器人導論 為教授三年級和四年級本科生設計和控制自動化機器人的計算基礎提供了急需的資源。作者採用經過課堂測試且易於理解的方法，逐步呈現進階的開發概念，並結合各種現實世界的例子以及機構、感測與驅動、計算和不確定性等基本概念。在整個過程中，作者平衡了硬體（機構、感測器、驅動器）和軟體（算法）在教學機器人自主性方面的影響。

    特色：
  • 嚴謹且經過課堂測試
  • 為具有線性代數、概率論、三角學和統計學的二年級理解能力的工程和計算機科學本科生撰寫
  • 文本中的QR碼引導讀者訪問線上講座視頻和動畫
  • 主題包括：機器人機構中的基本概念，如運動和抓取，以及由此產生的力；感測器和驅動器的操作原理；視覺和特徵檢測的基本算法；人工神經網絡的介紹，包括卷積和遞迴變體
  • 廣泛的附錄專注於基於項目的課程、相關數學領域、反向傳播、撰寫研究論文及其他主題
  • 在一個開源、平台無關的模擬環境（Webots）中不斷增長的練習庫

    • 作者簡介

    Nikolaus Correll is Associate Professor of Computer Science at the University of Colorado Boulder. Bradley Hayes is Assistant Professor of Computer Science at the University of Colorado Boulder. Christoffer Heckman is Assistant Professor of Computer Science at the University of Colorado Boulder. Alessandro Roncone is Assistant Professor of Computer Science at the University of Colorado Boulder.

    作者簡介(中文翻譯)

    尼古拉斯·科雷爾（Nikolaus Correll）是科羅拉多大學博爾德分校的計算機科學副教授。布拉德利·海斯（Bradley Hayes）是科羅拉多大學博爾德分校的計算機科學助理教授。克里斯托弗·赫克曼（Christoffer Heckman）是科羅拉多大學博爾德分校的計算機科學助理教授。亞歷山德羅·羅恩科內（Alessandro Roncone）是科羅拉多大學博爾德分校的計算機科學助理教授。

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