Koubaa Robot Operating System (ROS)

The Complete Reference (Volume 6)
Erscheinungsjahr 2021
ISBN: 978-3-030-75472-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 962, 269 Seiten, eBook

Reihe: Studies in Computational Intelligence

This book is the sixth volume of the successful book series on Robot Operating System: The Complete Reference. The objective of the book is to provide the reader with comprehensive coverage of the Robot Operating Systems (ROS) and the latest trends and contributed systems. ROS is currently considered as the primary development framework for robotics applications.There are seven chapters organized into three parts.Part I presents two chapters on the emerging ROS 2.0 framework; in particular, ROS 2.0 is become increasingly mature to be integrated into the industry. The first chapter from Amazon AWS deals with the challenges that ROS 2 developers will face as they transition their system to be commercial-grade. The second chapter deals with reactive programming for both ROS1 and ROS. In Part II, two chapters deal with advanced robotics, namely on the usage of robots in farms, and the second deals with platooning systems. Part III provides three chapters on ROS navigation. The first chapter deals with the use of deep learning for ROS navigation. The second chapter presents a detailed tuning guide on ROS navigation and the last chapter discusses SLAM for ROS applications. I believe that this book is a valuable companion for ROS users and developers to learn more ROS capabilities and features.

Zielgruppe

Research

Autoren/Hrsg.

Koubaa, Anis

Inhaltsverzeichnis

Part I. ROS 2.0: Developing Production-Grade Applications with ROS 2.- Reactive Programming of Robots with RxROS.- Part II. Advanced Robotic Systems.- ROS Integration of an Instrumented Bobcat T190 for the SEMFIRE project.- CopaDrive: an integrated ROS cooperative driving test and validation framework.- Part III. ROS Navigation.- Autonomous Navigation with Mobile Robots using Deep Learning and the Robot Operating System.- ROS Navigation Tuning Guide.- Mobile Robotics, SLAM, Bayesian Filter, Keyframe Bundle Adjustment and ROS Applications.

Über Autor(innen)

Prof. Anis Koubaa Prince Sultan University, Saudi Arabia