Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms. Este artículo no está disponible.
Correll, Nikolaus; Hayes, Bradley; Heckman, Christoffer; Roncone, Alessandro
5 valoraciones de Goodreads
Idioma: inglés
Editorial: The MIT Press, 2022
- Tapa dura
- Nuevo

Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
Vendedor de 5 estrellas
Vendedor de IberLibro desde 25 de marzo de 2015
No disponible
Tapa dura
Condición: Nuevo
EUR 78,50
Descripción del artículo del vendedor
In English.
N° de ref. del artículo ria9780262047555_new
- Título
- Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms
- Autor
- Correll, Nikolaus; Hayes, Bradley; Heckman, Christoffer; Roncone, Alessandro
- Editorial
- The MIT Press
- Año de publicación
- 2022
- Estado
- New
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 0262047551
- ISBN 13
- 9780262047555
- Peso del artículo
- 810 gramos
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)
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:
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Acerca del autor
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.
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