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Books on the topic 'Simultaneous localisation and mapping'

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Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Milford, Michael John. Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Berlin: Springer, 2008.

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2

Będkowski, Janusz. Large-Scale Simultaneous Localization and Mapping. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1972-5.

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3

Harold, Weinberg, and Bencivenga Roberto Ph D, eds. Introduction to brain topography. New York: Plenum Press, 1991.

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4

Fernández-Madrigal, Juan-Antonio. Simultaneous localization and mapping for mobile robots: Introduction and methods. Hershey, PA: Information Science Reference, 2013.

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5

Flavin, Nora. Cloning and characterisation of the bovine activin receptor type II gene (ActRII): Its localisation to chromosome 2 (BTA2) by somatic cell genetic analysis and the genotyping of an associated microsatelltie UCD2. Dublin: University College Dublin, 1996.

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6

Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer, 2010.

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7

Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer London, Limited, 2007.

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8

Adaptive Sampling With Mobile Wsn Simultaneous Robot Localisation And Mapping Of Paramagnetic Spatiotemporal Fields. Institution of Engineering & Technology (IET), 2011.

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9

Lewis, Frank L., Koushil Sreenath, Muhammad F. Mysorewala, and Dan O. Popa. Adaptive Sampling with Mobile WSN: Simultaneous Robot Localisation and Mapping of Paramagnetic Spatio-Temporal Fields. Institution of Engineering & Technology, 2011.

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10

Janusz Będkowski. Large-Scale Simultaneous Localization and Mapping. Springer, 2022.

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11

Simultaneous Localization and Mapping New Frontiers in Robotics. World Scientific Publishing Company, 2011.

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12

Nüchter, Andreas. 3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom. Springer London, Limited, 2008.

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13

Nüchter, Andreas. 3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom. Springer Berlin / Heidelberg, 2010.

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14

3d Robotic Mapping The Simultaneous Localization And Mapping Problem With Six Degrees Of Freedom. Springer, 2009.

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15

Montemerlo, Michael, and Sebastian Thrun. FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics. Springer London, Limited, 2007.

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16

Montemerlo, Michael, and Sebastian Thrun. FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics. Springer Berlin / Heidelberg, 2010.

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17

FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics (Springer Tracts in Advanced Robotics). Springer, 2007.

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18

Sanfeliu, Alberto, and Juan Andrade Cetto. Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building. Springer, 2010.

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19

Andrade-Cetto, Juan, and Alberto Sanfeliu. Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics). Springer, 2006.

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20

Gert, Pfurtscheller, and Lopes da Silva, F. H., 1935-, eds. Functional brain imaging. Toronto: Hans Huber Publishers, 1988.

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21

Tenney, James. Introduction to “Contributions toward a Quantitative Theory of Harmony”. Edited by Larry Polansky, Lauren Pratt, Robert Wannamaker, and Michael Winter. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252038723.003.0010.

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James Tenney presents the introduction to his 1979 essay “Contributions toward a Quantitative Theory of Harmony.” In this introduction, Tenney discusses the history of consonance/dissonance, paying attention to the semantic problem, relations between pitches, qualities of simultaneous aggregates, and contextual as well as operational and functional senses of consonance/dissonance. He also explores the structure of harmonic series aggregates, focusing on harmonic intersection and disjunction, harmonic density, and harmonic distance and pitch mapping. Finally, he considers problems of tonality by analyzing harmonic-melodic roots and the “tonic effect,” along with harmonic (chordal) roots, the “fundamental bass,” and a model of pitch perception in the auditory system. In an epilogue, Tenney describes new harmonic resources as well as prospects and limitations of his contributions.

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22

Erdem, Uğur Murat, Nicholas Roy, John J. Leonard, and Michael E. Hasselmo. Spatial and episodic memory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0029.

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The neuroscience of spatial memory is one of the most promising areas for developing biomimetic solutions to complex engineering challenges. Grid cells are neurons recorded in the medial entorhinal cortex that fire when rats are in an array of locations in the environment falling on the vertices of tightly packed equilateral triangles. Grid cells suggest an exciting new approach for enhancing robot simultaneous localization and mapping (SLAM) in changing environments and could provide a common map for situational awareness between human and robotic teammates. Current models of grid cells are well suited to robotics, as they utilize input from self-motion and sensory flow similar to inertial sensors and visual odometry in robots. Computational models, supported by in vivo neural activity data, demonstrate how grid cell representations could provide a substrate for goal-directed behavior using hierarchical forward planning that finds novel shortcut trajectories in changing environments.

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