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Zustand: New. pp. 116.

Taschenbuch. Zustand: Neu. Recognizing Intentions | Improving Human-Machine Collaboration by Recognizing Intentions | Daniel Aarno | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639093810 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Software and System Development Using Virtual Platforms | Full-System Simulation with Wind River Simics | Daniel Aarno (u. a.) | Taschenbuch | Englisch | 2014 | Elsevier Science | EAN 9780128007259 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, nlinfo[at]elsevier[dot]com | Anbieter: preigu.…

Paperback. Zustand: Brand New. 1st edition. 366 pages. 9.00x7.50x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Robot systems have been used extensively during thelast decades to provide automation solutions in anumber of areas. Most of the currently deployedautomation systems are limited in that the tasks theycan solve are required to be repetitive andpredicable. Therefore the robotics and artificialintelligence research communities have madesignificant research efforts to produce moreintelligent machines. Although significant progresshas been made towards achieving robots that caninteract in a human environment there are currentlyno system that comes close to achieving the reasoningcapabilities of humans.In order to reduce the complexity of the problem someresearchers have proposed an alternative to creatingfully autonomous robots capable of operating in humanenvironments. The proposed alternative is to allowfusion of human and machine capabilities.Segmentation and recognition of operator generatedmotions can be used to provide appropriate assistanceduring task execution in teleoperative andhuman-machine collaborative settings.This book describes research towards enablingimproved human-machine collaboration using intentionrecognition.…

Zustand: New. Print on Demand pp. 116 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam.

Zustand: New. PRINT ON DEMAND pp. 116.