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Control of multiple robots using vis...

Aranda, Miguel.

Control of multiple robots using vision sensors

Record Type:	Electronic resources : Monograph/item
Title/Author:	Control of multiple robots using vision sensorsby Miguel Aranda, Gonzalo Lopez-Nicolas, Carlos Sagues.
Author:	Aranda, Miguel.
other author:	Lopez-Nicolas, Gonzalo.
Published:	Cham :Springer International Publishing :2017.
Description:	xiii, 187 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	RobotsControl systems.
Online resource:	http://dx.doi.org/10.1007/978-3-319-57828-6
ISBN:	9783319578286$q(electronic bk.)

Control of multiple robots using vision sensors
Aranda, Miguel.

Control of multiple robots using vision sensors[electronic resource] /by Miguel Aranda, Gonzalo Lopez-Nicolas, Carlos Sagues. - Cham :Springer International Publishing :2017. - xiii, 187 p. :ill., digital ;24 cm. - Advances in industrial control,1430-9491. - Advances in industrial control..

Introduction -- Angle-based Navigation using the 1D Trifocal Tensor -- Vision-based Control for Nonholonomic Vehicles -- Controlling Mobile Robot Teams from 1D Homographies -- Control of Mobile Robot Formations using Aerial Cameras -- Coordinate-free Control of Multirobot Formations -- Conclusions and Directions for Future Research.

This monograph introduces novel methods for the control and navigation of mobile robots using multiple-1-d-view models obtained from omni-directional cameras. This approach overcomes field-of-view and robustness limitations, simultaneously enhancing accuracy and simplifying application on real platforms. The authors also address coordinated motion tasks for multiple robots, exploring different system architectures, particularly the use of multiple aerial cameras in driving robot formations on the ground. Again, this has benefits of simplicity, scalability and flexibility. Coverage includes details of: a method for visual robot homing based on a memory of omni-directional images a novel vision-based pose stabilization methodology for non-holonomic ground robots based on sinusoidal-varying control inputs an algorithm to recover a generic motion between two 1-d views and which does not require a third view a novel multi-robot setup where multiple camera-carrying unmanned aerial vehicles are used to observe and control a formation of ground mobile robots and three coordinate-free methods for decentralized mobile robot formation stabilization. The performance of the different methods is evaluated both in simulation and experimentally with real robotic platforms and vision sensors. Control of Multiple Robots Using Vision Sensors will serve both academic researchers studying visual control of single and multiple robots and robotics engineers seeking to design control systems based on visual sensors. Advances in industrial control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

ISBN: 9783319578286$q(electronic bk.)

Standard No.: 10.1007/978-3-319-57828-6doiSubjects--Topical Terms:

182098
Robots
--Control systems.

LC Class. No.: TJ211.35

Dewey Class. No.: 629.8

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245 1 0 $a Control of multiple robots using vision sensors $h [electronic resource] / $c by Miguel Aranda, Gonzalo Lopez-Nicolas, Carlos Sagues.
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490 1 $a Advances in industrial control, $x 1430-9491
505 0 $a Introduction -- Angle-based Navigation using the 1D Trifocal Tensor -- Vision-based Control for Nonholonomic Vehicles -- Controlling Mobile Robot Teams from 1D Homographies -- Control of Mobile Robot Formations using Aerial Cameras -- Coordinate-free Control of Multirobot Formations -- Conclusions and Directions for Future Research.
520 $a This monograph introduces novel methods for the control and navigation of mobile robots using multiple-1-d-view models obtained from omni-directional cameras. This approach overcomes field-of-view and robustness limitations, simultaneously enhancing accuracy and simplifying application on real platforms. The authors also address coordinated motion tasks for multiple robots, exploring different system architectures, particularly the use of multiple aerial cameras in driving robot formations on the ground. Again, this has benefits of simplicity, scalability and flexibility. Coverage includes details of: a method for visual robot homing based on a memory of omni-directional images a novel vision-based pose stabilization methodology for non-holonomic ground robots based on sinusoidal-varying control inputs an algorithm to recover a generic motion between two 1-d views and which does not require a third view a novel multi-robot setup where multiple camera-carrying unmanned aerial vehicles are used to observe and control a formation of ground mobile robots and three coordinate-free methods for decentralized mobile robot formation stabilization. The performance of the different methods is evaluated both in simulation and experimentally with real robotic platforms and vision sensors. Control of Multiple Robots Using Vision Sensors will serve both academic researchers studying visual control of single and multiple robots and robotics engineers seeking to design control systems based on visual sensors. Advances in industrial control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
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