Back to Search

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

AUTHOR Heckman, Christoffer; Hayes, Bradley; Correll, Nikolaus
PUBLISHER MIT Press (12/20/2022)
PRODUCT TYPE Hardcover (Hardcover)

Description
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)
  • Show More
    Product Format
    Product Details
    ISBN-13: 9780262047555
    ISBN-10: 0262047551
    Binding: Hardback or Cased Book (Sewn)
    Content Language: English
    More Product Details
    Page Count: 288
    Carton Quantity: 20
    Product Dimensions: 7.09 x 0.87 x 9.06 inches
    Weight: 1.49 pound(s)
    Feature Codes: Bibliography, Index, Price on Product, Illustrated
    Country of Origin: US
    Subject Information
    BISAC Categories
    Technology & Engineering | Robotics
    Technology & Engineering | Computer Science
    Technology & Engineering | Mechanical
    Dewey Decimal: 629.893
    Library of Congress Control Number: 2022010036
    Descriptions, Reviews, Etc.
    publisher marketing
    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)
  • Show More
    Your Price  $64.35
    Hardcover