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Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots. 2020 ed.
・ISBN 978-3-030-41807-6 hard EUR 119.99
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| 著者・編者 | Kucner, Tomasz Piotr / Lilienthal, Achim J. / Magnusson, Martin / Palmieri, Luigi / Srinivas Swaminathan, Chittaranjan, |
|---|---|
| シリーズ | (Cognitive Systems Monographs) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2020 |
| ページ数 | 151 pp. |
| 言語 | ENG |
| ニュース番号 | <A03-95361> |
解説
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.