Intelligent Autonomous Drones with Cognitive Deep Learning

Build AI-Enabled Land Drones with the Raspberry Pi 4

David Allen Blubaugh, Michael J. Findler, Steven D. Harbour, Benjamin Sears

  • Apress

  • Date de publication : 2022-10-31

Ce livre est accessible aux handicaps Voir les informations d'accessibilité
J'achète
66,05 €
Téléchargement | DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
Ajouter à ma liste d'envies
Gagnez  9,91 €  en recommandant ce livre avec Readzis

What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.

You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. 

Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability.

Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones.

What You’ll Learn
  • Examine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous drones
  • Look at software and hardware requirements
  • Understand unified modeling language (UML) and real-time UML for design
  • Study deep learning neural networks for pattern recognition
  • Review geo-spatial Information for the development of detailed mission planning within these hostile environments

Who This Book IsFor

Primarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.


Détails
Auteur
David Allen  Blubaugh , Michael J.  Findler , Steven D.  Harbour , Benjamin  Sears
Marque
Apress
Collection
n.c
Parution
2022-10-31
Pages
511 pages
EAN papier
9781484268025
Langue
Anglais
Informations ebook
EAN PDF
9781484268032
Prix
66,05 €
En savoir plus
Nb pages copiables 5
Nb pages imprimables 51
Taille du fichier 15852 Ko
Ce livre est accessible aux handicaps   Informations sur l'accessibilité
EAN EPUB
9781484268032
Prix
66,05 €
En savoir plus
Nb pages copiables 5
Nb pages imprimables 51
Taille du fichier 15104 Ko
Ce livre est accessible aux handicaps   Informations sur l'accessibilité
Compatibilité

mobile-and-tablet Pour vérifier la compatibilité avec vos appareils,
consultez la page d'aide

Avis clients

Suggestions personnalisées

Restez informé(e) des événements et promotions ebook

Paiements sécurisés

Paiements sécurisés