A moment measure model of landmarks for local homing navigation

Changmin Lee; Dae Eun Kim

doi:10.1007/978-3-319-43488-9_12

A moment measure model of landmarks for local homing navigation

Changmin Lee, Dae Eun Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Visual navigation in robotics is one of the challenging issues, and many navigation approaches are based on localization of a mobile robot in the environment. The snapshot model is a biologically inspired model of insect behaviour to return home and it shows a simple algorithm to compare the snapshot images at the current position and the destination, instead of complex localization process. Here, we propose a new homing navigation method based on a moment measure to characterize the snapshot image efficiently. The method uses range values or pixel values of surrounding landmarks. Then it defines a moment measure to evaluate the environmental features, or landmark distributions, and the measure forms a convex shape of landscape with respect to robot positions in the environment. Based on the landscape, the mobile robot can return home successfully. Range sensors or image sensors can sufficiently provide the landscape information. Our experimental results demonstrate that the method is effective even in real environments.

Original language	English
Title of host publication	From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings
Editors	John Hallam, Elio Tuci, Alexandros Giagkos, Myra Wilson
Publisher	Springer Verlag
Pages	126-137
Number of pages	12
ISBN (Print)	9783319434872
DOIs	https://doi.org/10.1007/978-3-319-43488-9_12
Publication status	Published - 2016
Event	14th International Conference on Simulation of Adaptive Behavior, SAB 2016 - Aberystwyth, United Kingdom Duration: 2016 Aug 23 → 2016 Aug 26

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9825 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	14th International Conference on Simulation of Adaptive Behavior, SAB 2016
Country	United Kingdom
City	Aberystwyth
Period	16/8/23 → 16/8/26

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2014R1A2A1A11053839).

Publisher Copyright:
© Springer International Publishing Switzerland 2016.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-43488-9_12

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Lee, C., & Kim, D. E. (2016). A moment measure model of landmarks for local homing navigation. In J. Hallam, E. Tuci, A. Giagkos, & M. Wilson (Eds.), From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings (pp. 126-137). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9825 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-43488-9_12

Lee, Changmin ; Kim, Dae Eun. / A moment measure model of landmarks for local homing navigation. From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings. editor / John Hallam ; Elio Tuci ; Alexandros Giagkos ; Myra Wilson. Springer Verlag, 2016. pp. 126-137 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A moment measure model of landmarks for local homing navigation",

abstract = "Visual navigation in robotics is one of the challenging issues, and many navigation approaches are based on localization of a mobile robot in the environment. The snapshot model is a biologically inspired model of insect behaviour to return home and it shows a simple algorithm to compare the snapshot images at the current position and the destination, instead of complex localization process. Here, we propose a new homing navigation method based on a moment measure to characterize the snapshot image efficiently. The method uses range values or pixel values of surrounding landmarks. Then it defines a moment measure to evaluate the environmental features, or landmark distributions, and the measure forms a convex shape of landscape with respect to robot positions in the environment. Based on the landscape, the mobile robot can return home successfully. Range sensors or image sensors can sufficiently provide the landscape information. Our experimental results demonstrate that the method is effective even in real environments.",

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Lee, C & Kim, DE 2016, A moment measure model of landmarks for local homing navigation. in J Hallam, E Tuci, A Giagkos & M Wilson (eds), From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9825 LNCS, Springer Verlag, pp. 126-137, 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Aberystwyth, United Kingdom, 16/8/23. https://doi.org/10.1007/978-3-319-43488-9_12

A moment measure model of landmarks for local homing navigation. / Lee, Changmin; Kim, Dae Eun.

From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings. ed. / John Hallam; Elio Tuci; Alexandros Giagkos; Myra Wilson. Springer Verlag, 2016. p. 126-137 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9825 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2014R1A2A1A11053839). Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

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N2 - Visual navigation in robotics is one of the challenging issues, and many navigation approaches are based on localization of a mobile robot in the environment. The snapshot model is a biologically inspired model of insect behaviour to return home and it shows a simple algorithm to compare the snapshot images at the current position and the destination, instead of complex localization process. Here, we propose a new homing navigation method based on a moment measure to characterize the snapshot image efficiently. The method uses range values or pixel values of surrounding landmarks. Then it defines a moment measure to evaluate the environmental features, or landmark distributions, and the measure forms a convex shape of landscape with respect to robot positions in the environment. Based on the landscape, the mobile robot can return home successfully. Range sensors or image sensors can sufficiently provide the landscape information. Our experimental results demonstrate that the method is effective even in real environments.

AB - Visual navigation in robotics is one of the challenging issues, and many navigation approaches are based on localization of a mobile robot in the environment. The snapshot model is a biologically inspired model of insect behaviour to return home and it shows a simple algorithm to compare the snapshot images at the current position and the destination, instead of complex localization process. Here, we propose a new homing navigation method based on a moment measure to characterize the snapshot image efficiently. The method uses range values or pixel values of surrounding landmarks. Then it defines a moment measure to evaluate the environmental features, or landmark distributions, and the measure forms a convex shape of landscape with respect to robot positions in the environment. Based on the landscape, the mobile robot can return home successfully. Range sensors or image sensors can sufficiently provide the landscape information. Our experimental results demonstrate that the method is effective even in real environments.

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ER -

Lee C, Kim DE. A moment measure model of landmarks for local homing navigation. In Hallam J, Tuci E, Giagkos A, Wilson M, editors, From Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings. Springer Verlag. 2016. p. 126-137. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-43488-9_12

A moment measure model of landmarks for local homing navigation

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