Deep Learning for Unmanned Systems /

This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not l...

Full description

Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Koubaa, Anis (Editor), Azar, Ahmad Taher (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:	1st ed. 2021.
Series:	Studies in Computational Intelligence, 984
Subjects:	Control engineering. Robotics. Mechatronics. Computational intelligence. Engineering-Data processing. Control, Robotics, Mechatronics. Computational Intelligence. Data Engineering. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Deep Learning for Unmanned Autonomous Vehicles: A Comprehensive Review
Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment
Reactive Obstacle Avoidance Method for a UAV
Guaranteed Performances for Learning-Based Control Systems using Robust Control Theory
A cascaded deep Neural Network for Position Estimation of Industrial Robots
Managing Deep Learning Uncertainty for Autonomous Systems
Uncertainty-Aware Autonomous Mobile Robot Navigation with Deep Reinforcement Learning
Deep Reinforcement Learning for Autonomous Mobile Networks in Micro-Grids
Reinforcement learning for Autonomous Morphing Control and Cooperative Operations of UAV Cluster
Image-Based Identification of Animal Breeds Using Deep Learning.