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Motion and sensing in electrosensory...

Solberg, James R.

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Motion and sensing in electrosensory systems.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Motion and sensing in electrosensory systems./
Author:	Solberg, James R.
Description:	313 p.
Notes:	Advisers: Kevin Lynch; Malcolm MacIver.
Contained By:	Dissertation Abstracts International68-11B.
Subject:	Engineering, Robotics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3284282
ISBN:	9780549295723

Motion and sensing in electrosensory systems.
Solberg, James R.

Motion and sensing in electrosensory systems. - 313 p.

Advisers: Kevin Lynch; Malcolm MacIver.

Thesis (Ph.D.)--Northwestern University, 2007.

Sensing is a fundamental operation for almost any motion-based system. We have chosen electrosensory systems as a platform to explore sensing and control in both artificial and biological systems. Electrosense is a convenient sensing modality because artificial electrosensory systems are relatively simple to implement, and weakly electric fish have some of the most well-documented sensorimotor pathways. In particular, active electrolocation is investigated, where the task is to estimate the location of a target using measurements from a self-generated electric field. The fundamentals of electrolocation are described first with a finite-element numerical approximation of the governing equations, and then simple models are used to predict electrosensory observations. Several belief maintenance schemes are employed to fuse sensor data and explicitly account for uncertainties in the position of the target. In the biological realm, a protocol for simulating the sensory acquisition and belief maintenance during prey-capture behavior in the weakly electric fish was developed. Using these simulations optimal sensing was investigated, and results provide insight into the interdependencies and co-evolution of sensing and motion systems of the weakly electric fish. In the artificial realm, an electrosensory robot capable of actively locating underwater targets by measuring perturbations in a self-generated electric field was built. Using seven different control algorithms, the robot can successfully locate nearby targets, as well as localize itself when placed in a pre-mapped environment, in both fresh and saltwater.

ISBN: 9780549295723Subjects--Topical Terms:

1018454
Engineering, Robotics.

Motion and sensing in electrosensory systems.
LDR:02663nam 2200313 a 45 001 954649
005 20110622
008 110622s2007 ||||||||||||||||| ||eng d
020 $a 9780549295723
035 $a (UMI)AAI3284282
035 $a AAI3284282
040 $a UMI $c UMI
100 1 $a Solberg, James R. $3 1278108
245 1 0 $a Motion and sensing in electrosensory systems.
300 $a 313 p.
500 $a Advisers: Kevin Lynch; Malcolm MacIver.
500 $a Source: Dissertation Abstracts International, Volume: 68-11, Section: B, page: 7638.
502 $a Thesis (Ph.D.)--Northwestern University, 2007.
520 $a Sensing is a fundamental operation for almost any motion-based system. We have chosen electrosensory systems as a platform to explore sensing and control in both artificial and biological systems. Electrosense is a convenient sensing modality because artificial electrosensory systems are relatively simple to implement, and weakly electric fish have some of the most well-documented sensorimotor pathways. In particular, active electrolocation is investigated, where the task is to estimate the location of a target using measurements from a self-generated electric field. The fundamentals of electrolocation are described first with a finite-element numerical approximation of the governing equations, and then simple models are used to predict electrosensory observations. Several belief maintenance schemes are employed to fuse sensor data and explicitly account for uncertainties in the position of the target. In the biological realm, a protocol for simulating the sensory acquisition and belief maintenance during prey-capture behavior in the weakly electric fish was developed. Using these simulations optimal sensing was investigated, and results provide insight into the interdependencies and co-evolution of sensing and motion systems of the weakly electric fish. In the artificial realm, an electrosensory robot capable of actively locating underwater targets by measuring perturbations in a self-generated electric field was built. Using seven different control algorithms, the robot can successfully locate nearby targets, as well as localize itself when placed in a pre-mapped environment, in both fresh and saltwater.
590 $a School code: 0163.
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
710 2 $a Northwestern University. $b Mechanical Engineering. $3 1018403
773 0 $t Dissertation Abstracts International $g 68-11B.
790 $a 0163
790 1 0 $a Freeman, Randy $e committee member
790 1 0 $a Hartmann, Mitra $e committee member
790 1 0 $a LaValle, Steve $e committee member
790 1 0 $a Lynch, Kevin, $e advisor
790 1 0 $a MacIver, Malcolm, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3284282