Image from Google Jackets

Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots / by Tomasz Piotr Kucner [y otros cuatro]

By: Kucner, Tomasz Piotr, autor.
Contributor(s): SpringerLink (Online service)
Material type: materialTypeLabelE-bookSeries: (Cognitive Systems Monographs, 1867-4925; 40); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Springer International Publishing, 2020Edition: First edition 2020.Description: 1 recurso en línea (XXV, 151 páginas) : 69 ilustraciones, 66 ilustraciones a color.ISBN: 9783030418083.Subject: Probabilidades | Robots móvilesOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Maps of Dynamics -- Modelling Motion Patterns with CT-Map -- Modelling Motion Patterns with CLiFF-Map -- Motion Planning using MoDs -- Closing Remarks.
Abstract: This book describes how robots can make sense of motion in their surroundings and use the patterns they observe to blend in better in dynamic environments shared with humans. The world around us is constantly changing. Nonetheless, we can find our way and aren't overwhelmed by all the buzz, since motion often follows discernible patterns. Just like humans, robots need to understand the patterns behind the dynamics in their surroundings to be able to efficiently operate e.g. in a busy airport. Yet robotic mapping has traditionally been based on the static world assumption, which disregards motion altogether. In this book, the authors describe how robots can instead explicitly learn patterns of dynamic change from observations, store those patterns in Maps of Dynamics (MoDs), and use MoDs to plan less intrusive, safer and more efficient paths. The authors discuss the pros and cons of recently introduced MoDs and approaches to MoD-informed motion planning, and provide an outlook on future work in this emerging, fascinating field. .
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA273 2020 EB (Browse shelf(Opens below)) Acceso electrónico eBook.23042088
Total holds: 0

Introduction -- Maps of Dynamics -- Modelling Motion Patterns with CT-Map -- Modelling Motion Patterns with CLiFF-Map -- Motion Planning using MoDs -- Closing Remarks.

This book describes how robots can make sense of motion in their surroundings and use the patterns they observe to blend in better in dynamic environments shared with humans. The world around us is constantly changing. Nonetheless, we can find our way and aren't overwhelmed by all the buzz, since motion often follows discernible patterns. Just like humans, robots need to understand the patterns behind the dynamics in their surroundings to be able to efficiently operate e.g. in a busy airport. Yet robotic mapping has traditionally been based on the static world assumption, which disregards motion altogether. In this book, the authors describe how robots can instead explicitly learn patterns of dynamic change from observations, store those patterns in Maps of Dynamics (MoDs), and use MoDs to plan less intrusive, safer and more efficient paths. The authors discuss the pros and cons of recently introduced MoDs and approaches to MoD-informed motion planning, and provide an outlook on future work in this emerging, fascinating field. .

There are no comments on this title.

to post a comment.
Share