000			02950nam a2200433 i 4500
710	2		_aSpringerLink (Online service) _9106996
999			_c119406 _d119406
001			119406
003			ES-MaUEC
005			20230102113947.0
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007			cr nn nnnaamaa
008			200328s2020 gw a s |||| 0|eng d
020			_a9783030418083
024	7		_a10.1007/978-3-030-41808-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA273 _b2020 EB
100	1		_aKucner, Tomasz Piotr _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673635
245	1	0	_aProbabilistic Mapping of Spatial Motion Patterns for Mobile Robots _cby Tomasz Piotr Kucner [y otros cuatro]
250			_aFirst edition 2020.
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XXV, 151 páginas) _b69 ilustraciones, 66 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aCognitive Systems Monographs _x1867-4925 _v40
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aIntroduction -- Maps of Dynamics -- Modelling Motion Patterns with CT-Map -- Modelling Motion Patterns with CLiFF-Map -- Motion Planning using MoDs -- Closing Remarks.
520	3		_aThis 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. .
988			_aSpringer_Robotics_31032020
650		7	_2embne _9405075 _aProbabilidades
650		7	_2embne _9160722 _aRobots móviles
776	0	8	_iPrinted edition: _z9783030418076
776	0	8	_iPrinted edition: _z9783030418090
776	0	8	_iPrinted edition: _z9783030418106
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-41808-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2020 _dz _ek _zSI