000			02138cam a22003858i 4500
999			_c16736 _d16736
001			20453542
003			AUCL
005			20200110121557.0
008			180416s2018 flu b 001 0 eng
010			_a 2018017262
020			_a9780815378686 (hardback : acid-free paper)
020			_z9781351231794 (ebook)
040			_aDLC _beng _erda _cAUI
042			_apcc
050	0	0	_aTJ211.35 _b.A73 2018
082	0	0	_a629.892632 ARA _223
100	1		_aArana-Daniel, Nancy, _eauthor.
245	1	0	_aNeural networks for robotics : an engineering perspective _ban engineering perspective / _cNancy Arana-Daniel, Carlos Lopez-Franco, Alma Y. Alanis.
263			_a1808
264		1	_aBoca Raton, FL : _bCRC Press/Taylor & Francis Group, _c2019.
300			_axvii;209 p.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
500			_a"A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."
504			_aIncludes bibliographical references and index.
520			_aThe book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control-- _cProvided by publisher.
650		0	_aRobots _xControl systems.
650		0	_aNeural networks (Computer science)
700	1		_aLopez-Franco, Carlos, _eauthor.
700	1		_aAlanis, Alma Y., _eauthor.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK