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001 978-3-319-26327-4
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007 cr nn 008mamaa
008 160206s2015 gw | s |||| 0|eng d
020 _a9783319263274
_9978-3-319-26327-4
024 7 _a10.1007/978-3-319-26327-4
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
245 1 0 _aHandling Uncertainty and Networked Structure in Robot Control
_h[electronic resource] /
_cedited by Lucian Busoniu, Levente Tam�as.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXXVIII, 388 p. 172 illus., 26 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v42
505 0 _aFrom the Contents: Part I Learning Control in Unknown Environments -- Robot Learning for Persistent Autonomy -- The Explore-Exploit Dilemma in Nonstationary Decision Making under Uncertainty.- Part II Dealing with Sensing Uncertainty -- Observer Design for Robot Manipulators via Takagi-Sugeno Models and Linear Matrix Inequalities.- Part III Control of Networked and Interconnected Robots -- Vision-based quadcopter navigation in structured environments.
520 _aThis book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describes learning control to address environmental uncertainty. Part II discusses state estimation, active sensing, and complex scenario perception to tackle sensing uncertainty. Part III completes the book with control of networked robots and multi-robot teams. Each chapter features in-depth technical coverage and case studies highlighting the applicability of the techniques, with real robots or in simulation. Platforms include mobile ground, aerial, and underwater robots, as well as humanoid robots and robot arms. Source code and experimental data are available at http://extras.springer.com. The text gathers contributions from academic and industry experts, and offers a valuable resource for researchers or graduate students in robot control and perception. It also benefits researchers in related areas, such as computer vision, nonlinear and learning control, and multi-agent systems.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aAutomation.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aRobotics and Automation.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aBusoniu, Lucian.
_eeditor.
700 1 _aTam�as, Levente.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319263250
830 0 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v42
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26327-4
912 _aZDB-2-ENG
942 _cEBK
999 _c59044
_d59044