Parallel and Distributed Map Merging and Localization is popular PDF and ePub book, written by Rosario Aragues in 2015-10-31, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Parallel and Distributed Map Merging and Localization can be Read Online from any device for your convenience.
Parallel and Distributed Map Merging and Localization Book PDF Summary
This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them. In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level.
Detail Book of Parallel and Distributed Map Merging and Localization PDF
- Author : Rosario Aragues
- Release : 31 October 2015
- Publisher : Springer
- ISBN : 9783319258867
- Genre : Computers
- Total Page : 122 pages
- Language : English
- PDF File Size : 17,6 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Parallel and Distributed Map Merging and Localization by Rosario Aragues, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.