Handling Uncertainty and Networked Structure in Robot Control

Häftad, Engelska, 2018

AvLucian Bușoniu,Levente Tamás,Lucian Busoniu,Levente Tamas,Lucian Bușoniu,Lucian Bu¿oniu

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Thisbook focuses on two challenges posed in robot control by the increasingadoption of robots in the everyday human environment: uncertainty and networkedcommunication.

Produktinformation

Utgivningsdatum2018-03-30
Mått155 x 235 x 23 mm
Vikt628 g
FormatHäftad
SpråkEngelska
SerieStudies in Systems, Decision and Control
Antal sidor388
FörlagSpringer International Publishing AG
ISBN9783319799322

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LucianBusoniu received the M.Sc. degree (valedictorian) from the Technical Universityof Cluj-Napoca, Romania, in 2003 and the Ph.D. degree (cum laude) from theDelft University of Technology, the Netherlands, in 2009. He has held researchpositions in the Netherlands and France, and is currently an associateprofessor with the Department of Automation at the Technical University ofCluj-Napoca. His fundamental interests include planning-based methods fornonlinear optimal control, reinforcement learning and dynamic programming withfunction approximation, and multiagent systems; while his practical focus isapplying these techniques to robotics. He has coauthored a book and more than50 papers and book chapters on these topics. He was the recipient of the 2009Andrew P. Sage Award for the best paper in the IEEE Transactions on Systems,Man, and Cybernetics. Levente Tamas received the M.Sc. (valedictorian) and the Ph.D.degree in electrical engineering from TechnicalUniversity of Cluj-Napoca,Romania, in 2005 and 2010, respectively. He took part in several postdoctoralprograms dealing with 3D perception and robotics, the most recent one spent atthe Bern University of Applied Sciences, Switzerland. He is currently with theDepartment of Automation, Technical University of Cluj-Napoca, Romania. Hisresearch focuses on 3D perception and planning for autonomous mobile robots,and has resulted in several well ranked conference papers, journal articles, andbook chapters in this field.

From 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.