LEADER 05070nam 22008415 450 001 996465777303316 005 20200704045537.0 010 $a3-540-45124-2 024 7 $a10.1007/3-540-45124-2 035 $a(CKB)1000000000016854 035 $a(SSID)ssj0000324352 035 $a(PQKBManifestationID)11236841 035 $a(PQKBTitleCode)TC0000324352 035 $a(PQKBWorkID)10322745 035 $a(PQKB)10458854 035 $a(DE-He213)978-3-540-45124-2 035 $a(MiAaPQ)EBC3072573 035 $a(PPN)155204777 035 $a(EXLCZ)991000000000016854 100 $a20121227d2001 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aLearning-Based Robot Vision$b[electronic resource] $ePrinciples and Applications /$fby Josef Pauli 205 $a1st ed. 2001. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2001. 215 $a1 online resource (IX, 292 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v2048 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-42108-4 320 $aIncludes bibliographical references and index. 327 $aCompatibilities for Object Boundary Detection -- Manifolds for Object and Situation Recognition -- Learning-Based Achievement of RV Competences -- Summary and Discussion. 330 $aIndustrial robots carry out simple tasks in customized environments for which it is typical that nearly all e?ector movements can be planned during an - line phase. A continual control based on sensory feedback is at most necessary at e?ector positions near target locations utilizing torque or haptic sensors. It is desirable to develop new-generation robots showing higher degrees of autonomy for solving high-level deliberate tasks in natural and dynamic en- ronments. Obviously, camera-equipped robot systems, which take and process images and make use of the visual data, can solve more sophisticated robotic tasks. The development of a (semi-) autonomous camera-equipped robot must be grounded on an infrastructure, based on which the system can acquire and/or adapt task-relevant competences autonomously. This infrastructure consists of technical equipment to support the presentation of real world training samples, various learning mechanisms for automatically acquiring function approximations, and testing methods for evaluating the quality of the learned functions. Accordingly, to develop autonomous camera-equipped robot systems one must ?rst demonstrate relevant objects, critical situations, and purposive situation-action pairs in an experimental phase prior to the application phase. Secondly, the learning mechanisms are responsible for - quiring image operators and mechanisms of visual feedback control based on supervised experiences in the task-relevant, real environment. This paradigm of learning-based development leads to the concepts of compatibilities and manifolds. Compatibilities are general constraints on the process of image formation which hold more or less under task-relevant or accidental variations of the imaging conditions. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v2048 606 $aApplication software 606 $aOptical data processing 606 $aRobotics 606 $aAutomation 606 $aComputer graphics 606 $aArtificial intelligence 606 $aControl engineering 606 $aMechatronics 606 $aComputer Applications$3https://scigraph.springernature.com/ontologies/product-market-codes/I23001 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000 615 0$aApplication software. 615 0$aOptical data processing. 615 0$aRobotics. 615 0$aAutomation. 615 0$aComputer graphics. 615 0$aArtificial intelligence. 615 0$aControl engineering. 615 0$aMechatronics. 615 14$aComputer Applications. 615 24$aImage Processing and Computer Vision. 615 24$aRobotics and Automation. 615 24$aComputer Graphics. 615 24$aArtificial Intelligence. 615 24$aControl, Robotics, Mechatronics. 676 $a629.892637 700 $aPauli$b Josef$4aut$4http://id.loc.gov/vocabulary/relators/aut$0545742 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465777303316 996 $aLearning-based robot vision$9887573 997 $aUNISA