000			03292nam a22004215i 4500
001			u373795
003			SIRSI
005			20160812084203.0
007			cr nn 008mamaa
008			100301s2010 gw | s |||| 0|eng d
020			_a9783642103452 _9978-3-642-10345-2
040			_cMX-MeUAM
050		4	_aTJ210.2-211.495
050		4	_aT59.5
082	0	4	_a629.892 _223
100	1		_aWallgrün, Jan Oliver. _eauthor.
245	1	0	_aHierarchical Voronoi Graphs _h[recurso electrónico] : _bSpatial Representation and Reasoning for Mobile Robots / _cby Jan Oliver Wallgrün.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXXIII, 218 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aRobot Mapping -- Voronoi-Based Spatial Representations -- Simplification and Hierarchical Voronoi Graph Construction -- Voronoi Graph Matching for Data Association -- Global Mapping: Minimal Route Graphs Under Spatial Constraints -- Experimental Evaluation -- Conclusions and Outlook.
520			_aWhat is space? Is there space when there are objects to occupy it or is there space only when there are no objects to occupy it? Can there be space without objects? These are old philosophical questions that concern the ontology of space in the philosophical sense of ‘ontology’ – what is the nature of space? Cognitive science in general and arti?cial intelligence in particular are less c- cerned with the nature of things than with their mental conceptualizations. In spatial cognition research we address questions like What do we know about space? How is space represented? What are the representational entities? What are the rep- sentational structures? Answers to these questions are described in what is called ontologies in arti?cial intelligence. Different tasks require different knowledge, and different representations of knowledge facilitate different ways of solving problems. In this book, Jan Oliver Wallgrün develops and investigates representational structures to support tasks of autonomous mobile robots, from the acquisition of knowledge to the use of this knowledge for navigation. The research presented is concerned with the robot mapping problem, the pr- lem of building a spatial representation of an environment that is perceived by s- sors that only provide incomplete and uncertain information; this information usually needs to be related to other imprecise or uncertain information. The routes a robot can take can be abstractly described in terms of graphs where alternative routes are represented by alternative branches in these route graphs.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650	1	4	_aEngineering.
650	2	4	_aRobotics and Automation.
650	2	4	_aArtificial Intelligence (incl. Robotics).
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642103025
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-10345-2
596			_a19
942			_cLIBRO_ELEC
999			_c201675 _d201675