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Handling Uncertainty and Networked Structure in Robot Control de Lucian Bușoniu

Handling Uncertainty and Networked Structure in Robot Control: Studies in Systems, Decision and Control, cartea 42

Editat de Lucian Bușoniu, Levente Tamás
en Limba Engleză Hardback – 16 feb 2016
Thisbook focuses on two challenges posed in robot control by the increasingadoption of robots in the everyday human environment: uncertainty and networkedcommunication. PartI of the book describes learning control to address environmental uncertainty.Part II discusses state estimation, active sensing, and complex scenarioperception to tackle sensing uncertainty. Part IIIcompletes the book with control of networked robots and multi-robot teams.
Each chapter features in-depth technical coverage and case studieshighlighting the applicability of the techniques, with real robots or insimulation. Platforms include mobile ground, aerial, and underwater robots, aswell as humanoid robots and robot arms. Source code and experimental data areavailable 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 robotcontrol and perception. It also benefits researchers in related areas, such ascomputer vision, nonlinear and learning control, and multi-agent systems.
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Specificații

ISBN-13: 9783319263250
ISBN-10: 3319263250
Ilustrații: XXVIII, 388 p. 172 illus., 146 illus. in color. With online files/update.
Dimensiuni: 155 x 235 mm
Greutate: 0.76 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Systems, Decision and Control

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

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.

Notă biografică

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.

Textul de pe ultima copertă

Thisbook focuses on two challenges posed in robot control by the increasingadoption of robots in the everyday human environment: uncertainty and networkedcommunication. PartI of the book describes learning control to address environmental uncertainty.Part II discusses state estimation, active sensing, and complex scenarioperception to tackle sensing uncertainty. Part IIIcompletes the book with control of networked robots and multi-robot teams.
Each chapter features in-depth technical coverage and case studieshighlighting the applicability of the techniques, with real robots or insimulation. Platforms include mobile ground, aerial, and underwater robots, aswell as humanoid robots and robot arms. Source code and experimental data areavailable 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 robotcontrol and perception. It also benefits researchers in related areas, such ascomputer vision, nonlinear and learning control, and multi-agent systems.

Caracteristici

Presents in-depth coverage of a range of algorithms, which readers can implement and modify for their own systems Demonstrates practical investigations and case studies that highlight the applicability of the techniques Describes a selection of modern methods, offering readers up-to-date means of tackling uncertainty and network structure in robot control Provides additional electronic material, such as source code and experimental data Includes supplementary material: sn.pub/extras